Publications

Books

Refereed Journal Articles

Refereed Book Chapters

Refereed Conference Papers

Refereed Workshop Papers

Refereed Extended Abstracts

Technical Reports

Tutorials

Posters and Presentations

See also: Publications by Year, DBLP, Google Scholar, ResearchGate

Dissertation

Learning classifiers from distributed, autonomous, semantically heterogeneous data sources

Books

Das, S., Caragea, D., Welch, S.M. and Hsu, W.H. (Eds.) Computational Methodologies in Gene Regulatory Networks, IGI Publishers, New York. 2009.

Refereed Journal Articles

Prabesh Pathak, Prabesh Poudel, Sankardas Roy, and Doina Caragea (2021) Leveraging attention-based deep neural networks for security vetting of Android applications. EAI Endorsed Transactions on Security and Safety). In press.
Meenal Chaudhari, Niraj Thapa, Hamid Ismail, Sandhya Chopade, Doina Caragea, Maja Köhn, Robert H. Newman, and Dukka B. KC. (2021) DTL-DephosSite: Deep Transfer Learning Based Approach to Predict Dephosphorylation Sites. Frontiers in Cell and Developmental Biology 9 (2021): 1524.
Raju Bheemanahalli, Chaoxin Wang, Elfadil Bashir, Anuj Chiluwal, Meghnath Pokharel, Ramasamy Perumal, Naghmeh Moghimi, Troy Ostmeyer, Doina Caragea, S.V. Krishna Jagadish (2021) Classical phenotyping and deep learning concur on genetic control of stomatal density and area in sorghum. Plant Physiology, kiab174, 2021.
Nicole M. Wood, Sierra Davis, Karen Lewing, Janelle Noel-MacDonnell, Earl F. Glynn, Doina Caragea, and Mark A. Hoffman (2021) Aligning EHR data for pediatric leukemia with standard protocol therapy. PCO Clinical Cancer Informatics, 5 (2021): 239-251.
Muhammad Imran, Ferda Ofli, Doina Caragea, and Antonio Torralba (2020) Using AI and social media multimodal content for disaster response and management: Opportunities, challenges, and future direction. Information Processing \& Management,
Volume 57, Issue 5, 102261.
Chaoxin Wang, Xukun Li, Doina Caragea, Raju Bheemanahalli and Krishna Jagadish ((2020) Root anatomy based on root cross-section image analysis with deep learning. Computers and Electronics in Agriculture, Vol. 175, Aug. 2020, 105549.
Li, X., Caragea, D., Zhang, H., Imran, M. (2019) Localizing and quantifying infrastructure damage using class activation mapping approaches. Social Network Analysis and Mining (SNAM), 9(1):44, 2019.
Mazloom, R., Li, H., Caragea, D., Caragea, C., Imran, M. (2019) A hybrid domain adaptation approach for identifying crisis-relevant tweets. International Journal of Information Systems for Crisis Response and Management (IJISCRAM), 11(2):1–19, 2019.
Li, H., Sopova, O., Caragea, D., Caragea, C. (2019) Domain Adaptation for Crisis Data Using Correlation Alignment and Self-Training. International Journal of Information Systems for Crisis Response and Management (IJISCRAM), 10(4), 1-20, 2019.
Li, H., Caragea, D., Caragea, C. and Herndon, N. (2018). Disaster Response Aided by Tweet Classification with a Domain Adaptation Approach. In: Journal of Contingencies and Crisis Management (JCCM), Special Issue on HCI in Critical Systems. Vol. 26(1), Pages 16-27.
Noll, L.W., Worley J.N., Yang, X., Shridhar, P.B., Ludwig, J.B., Shi, X., Bai, J., Caragea, D., Meng, J., and TG Nagaraja (2018). Comparative genomics reveals differences in mobile virulence genes of Escherichia coli O103 pathotypes of bovine fecal origin In: PLoS ONE 13(2): e0191362.
Lance W Noll, Jay N Worley, Xun Yang, Pragathi B Shridhar, Jianfa Bai, Jianghong Meng, Caragea, D. and TG Nagaraja (2017). Draft Genome Sequences of Enterohemorrhagic Escherichia coli O103: H2 Strains Isolated from Feces of Feedlot Cattle In: Genome announcements, Vol. 5, Issue 19, pages e00094-17
Lance W Noll, Jay N Worley, Xun Yang, Pragathi B Shridhar, Jianfa Bai, Jianghong Meng, Caragea, D. and TG Nagaraja (2017). Draft Genome Sequences of Enteropathogenic Escherichia coli O103 Strains Isolated from Feces of Feedlot Cattle In: Genome announcements, Vol. 5, Issue 21, pages e00387-17
Stanescu, A. and Caragea, D. (2017). An empirical study of self-training and data balancing techniques for splice site prediction. International Journal of Bioinformatics Research and Applications. Volume 13, No. 1, pp. 40 - 61, February 2017.
Neppalli, K., Caragea, C., Caragea, D., Medeiros, M.C., Tapia, A. and Halse, S. (2016).Predicting Tweet Retweetability during Hurricane Disasters. International Journal of Information Systems for Crisis Response and Management (IJISCRAM). Vol. 3, no. 8, pages 32-50.
Herndon, N., Caragea, D. (2016). An evaluation of approaches for using unlabeled data with domain adaptation. In: Network Modeling Analysis in Health Informatics and Bioinformatics. 5(25):1-12, 2016.
Tangirala, K., Herndon, N. and Caragea, D. (2016). A Comparative Analysis between k-mers and Community Detection-based Features for the Task of Protein Classification. In: Special Issue of Transactions on Nanobioscience. Vol. 15, Issue 2, pp. 84 - 92, March 2016.
Herndon, N. and Caragea, D. (2016). A Study of Domain Adaptation Classifiers Derived from Logistic Regression for the Task of Splice Site Prediction. In: Special Issue of Transactions on Nanobioscience. Vol. 15, Issue 2, pp. 75-83, March 2016.
Stanescu, A., Tangirala, K. and Caragea, D. (2016). Predicting Alternatively Spliced Exons Using Semi-supervised Learning. In: International Journal on Data Mining and Bioinformatics (IJDMB) Vol. 14, No. 1, pages 1-21.
Stanescu, A., and Caragea, D. (2015). An empirical study of ensemble-based semi-supervised learning approaches for imbalanced splice site datasets. In: BMC Systems Biology supplement. 9(Suppl 5):S1 .
Zhang, S., Ou, X., and Caragea, D. (2015). Predicting Cyber Risks through National Vulnerability Database , Information Security Journal: A Global Perspective. Vol. 24, Issue 4-6, 2015.
Zhao, C., Navarro Escalante, L., Benatti, T., Qu, J., Chellapilla, S., Waterhouse, R. M., . . ., Caragea, D., … Richards, S. (2015). A Massive Expansion of Effector Genes Underlies Gall-Formation in the Wheat Pest (Mayetiola destructor). Current Biology, Volume 25, Issue 5, p613–620.
Carolan, J.C., Caragea, D., Reardon, K.T., Mutti, N.S., Pappan, K., Dittmer, N, Cui, F., Reeck, G.R, Castaneto, M., Poulain, J., Dossat, C., Wilkinson, T.L., Tagu, D., Reese, J.C. and Edwards, O.R. (2011). Predicted effector molecules in the salivary secretome of the pea aphid (Acyrthosiphon pisum) – a dual transcriptomic/proteomic approach. Journal of Proteome Research, 2011 Apr 1;10(4):1505-18.
Caragea, C., Caragea, D., Silvescu, A., and Honavar, V. (2010). Semi-Supervised Prediction of Protein Subcellular Localization Using Abstraction Augmented Markov Models , Special Issue on Machine Learning in Computational Biology (MLCB), BMC Bioinformatics. 2010 Oct 26;11 Suppl 8:S6.
Steller, M., Kambhampati, S., and Caragea, D. (2010) Comparative analysis of expressed sequence tags from three castes and two life stages of the termite Reticulitermes flavipes, BMC Genomics 2010, 11:463.
Kim, H.S., Murphy, T., Xia, J., Caragea, D., Park, Y., Beeman, R., Lorenzen, M., Manak, J., Butcher, S. and Brown, S. (2010). BeetleBase in 2010: revisions to provide comprehensive genomic information for Tribolium castaneum. In: Journal of Nucleic Acid Research (NAR), 2010, Vol. 38, Database issue D437-D442.
Travers, S. E., Tang, Z., Caragea, D., Garrett, K.A., Hulbert, S. H. , Leach, J. E. , Bai , J., Saleh, A., Knapp, A.K., Fay, P.A., Nippert, J., Schnable, P.S., and Smith, M.D. (2010) Spatial and temporal variation of big bluestem (Andropogon gerardii) transcription profiles with climate change. In: Journal of Ecology, 2010, 98, 374-383. Selected as Editor's Cho ice for March 2010 (Journal of Ecology, March 2010).
Xia, J., Caragea, D. and Brown, S.J. (2010). Prediction of alternatively spliced exons using support vector machines. In: International Journal on Data Mining and Bioinformatics (IJDMB), Vol. 4, No. 4, 411-430.
Caragea, D., Silvescu, A., and Honavar, V. (2004). Invited Paper. A Framework for Learning from Distributed Data Using Sufficient Statistics and its Application to Learning Decision Trees. In: International Journal of Hybrid Intelligent Systems. Vol. 1, No. 2, pp. 80-89.

Refereed Book Chapters

Caragea, D. and Xinming, Ou (2017). Big Data Analytics for Mobile App Security. In: Big Data Data Analytics in Cybersecurity (Data Analytics Applications) 1st Edition, Editors Onur Savas and Julia Deng. To appear.
Herndon, N. and Caragea, D. (2015). Empirical Study of Domain Adaptation Algorithms on the Task of Splice Site Prediction. Invited paper. In: Lecture Notes in Communications in Computer and Information Science (CCIS), Springer-Verlag Berlin Heidelberg.
Herndon, N. and Caragea, D. (2014). Predicting Protein Localization Using a Domain Adaptation Approach. Invited paper. In: Lecture Notes in Communications in Computer and Information Science (CCIS) 452, Springer-Verlag Berlin Heidelberg, pp. 191-206.
Caragea, D. and Honavar, V. (2009). Learning Classifiers from Distributed Data Sources. In: Encyclopedia of Database Technologies and Applications, 2nd Ed. Ferraggine, V.E., Doorn, J.H., and Rivero, L.C. (Eds.), pp. 589-596.
Honavar, V. and Caragea, D. (2009). Towards Semantics-Enabled Infrastructure for Knowledge Acquisition from Distributed Data. In: Next Generation of Data Mining. Eds.: Kargupta, H., Han, J., Yu, P., Motwani, R., and Kumar, V. CRC Press. Ch. 16, pp. 317-337. Invited Chapter.
Paradesi, M.S.R., Caragea, D., and Hsu, W.H. (2009). Incorporating Graph Features for Predicting Protein-Protein Interactions. In: Biological Data Mining in Protein Interaction Networks. Eds.: X.-L. Li and S.-K. Ng. IGI Publishers, pp. 45-63.
Caragea, D. and Honavar, V. (2009). Knowledge Acquisition from Semantically Heterogeneous Data. In: Encyclopedia of Data Warehousing and Mining, Second Edition, Wang, J. (Ed.). IGI Publishers, pp. 1110-1116.
Caragea, D., Cook, D., Wickham, H., and Honavar, V. (2008). Invited Chapter. Visual Methods for Examining SVM Classifiers. In: Visual Data Mining: Theory, Techniques, and Tools for Visual Analytics. Springer, LNCS Volume 4404, pp. 136 - 153.
Caragea, D., Silvescu, A., and Honavar, V. (2001). Invited Chapter. Towards a Theoretical Framework for Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources. In: Emerging Neural Architectures Based on Neuroscience. Berlin: Springer-Verlag, pp. 547-559.

Refereed Conference Papers

Sarthak Khanal and Doina Caragea (2021) Multi-task Learning to Enable Location Mention Identification in the Early Hours of a Crisis Event. The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), Findings. In press.
Sarthak Khanal, Rus Refati, Kyle Glandt, Doina Caragea, Sifan Xu, and Chien-fei Chen (2021) Using Content Analysis and Machine Learning to Identify COVID-19 Information Relevant to Low-income Households on Social Media. The 14th IEEE International Conference on Social Computing and Networking (IEEE SocialCom 2021). In press.
Soudabeh Taghian Dinani and Doina Caragea (2021) Disaster Image Classification Using Capsule Networks. The International Joint Conference on Neural Networks (IJCNN 2021). In press.
Kyle Glandt, Sarthak Khanal, Yingjie Li, Doina Caragea, and Cornelia Caragea (2021) Stance Detection in COVID-19 Tweets. The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), pp. 1596-1611.
Nawaf Alharbi and Doina Caragea (2021) Cross-Domain Self-Attentive Sequential Recommendations. Proceedings of the 2nd International Conference on Data Science and Applications (ICDSA 2021), April 2021. In press.
Nawaf Alharbi and Doina Caragea (2021) Cross-Domain Recommender System based on Neural Collaborative Filtering. Proceedings of the 17th International Conference on Machine Learning and Data Mining (MLDM 2021). June 2021. In press.
Tiberiu Sosea, Iustin Sarbu, Cornelia Caragea, Doina Caragea, and Traian Rebedea (2021) Using the Image-Text Relationship to Improve Multimodal Disaster Tweet Classification. Proceedings of the 18th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2021). In press.
HongMin Li, Doina Caragea, and Cornelia Caragea (2021) Combining Self-training with Deep Learning for Disaster Tweet Classification. Proceedings of the 18th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2021). In press.
Krutarth Patel, Cornelia Caragea, Doina Caragea, and C. Lee Giles. (2021) Author Homepage Discovery in CiteSeerX. Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-2021), February 2021, pp. 15146-15155. {Deployed Application Award}.
Doina Caragea, Mark Chen, Theodor Cojoianu, Mihai Dobri, Kyle Glandt, and George Mihaila (2020) Identifying FinTech Innovations Using BERT. Proceedings of the 20th IEEE Conference on Big Data, December 2020, pp. 1117-1126.
Xukun Li and Doina Caragea (2020) Domain Adaptation with Reconstruction for Disaster Tweet Classification. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1561-1564.
Xukun Li and Doina Caragea (2020) Improving Disaster-related Tweet Classification with a Multimodal Approach. Proceedings of the 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2020).
Nasik Muhammad Nafi, Avishek Bose, Sarthak Khanal, Doina Caragea, and William H. Hsu (2020) Abstractive Text Summarization of Disaster-Related Documents. Proceedings of the 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2020).
Dewan Chaulagain, Prabesh Pathak, Prabesh Prabesh, Sankardas Roy, Doina Caragea, Guojun Liu and Xinming Ou (2020) Hybrid Analysis of Android Apps for Security Vetting using Deep Learning. Proceedings of the IEEE Conference on Communications and Network Security (CNS 2020), pp. 1-9.
Jishnu Ray Chowdhury, Cornelia Caragea, and Doina Caragea (2020) On Identifying Hashtags in Disaster Twitter Data. Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence. Vol. 34, No. 01, pp. 498-506.
Jishnu Ray Chowdhury, Cornelia Caragea, and Doina Caragea (2020) Cross-Lingual Disaster-related Multi-label Tweet Classification with Manifold Mixup. Proceedings of The 2020 ACL Student Research Workshop (SRW) to be held in conjunction with ACL 2020, Seattle, Washington, pp. 292-298.
Yuping Li, Doina Caragea, Lawrence Hall, and Xinming Ou (2020) Experimental Study of Machine Learning based Malware Detection Systems' Practical Utility. HICSS Symposium on Cybersecurity Big Data Analytics, in conjunction with the 2020 Hawaii International Conference on System Sciences (HICSS 2020), Wailea, Hawaii.
Alfs, E., Caragea, D., Chaulagain, D., Roy, S., Albin, N. and Poggi-Corradini, P. (2019) Identifying android malware using network-based approaches. In: Proceedings of the International Symposium on Foundations of Open Source Intelligence and Security Informatics (FOSINT-SI 2019), In conjunction with ASONAM 2019, Vancouver, CA, 2019.
Li, X., Caragea, D., Caragea, C., Imran, M., and Olfi, F. (2019) Identifying Disaster Damage Images Using a Domain Adaptation Approach. In: Proceedings of the 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019), Valencia, Spain. [CoRe Paper.] Best Insight Paper Award.
Li, Y., Park, S.Y., Caragea, C. and Caragea, D. (2019) Sympathy Detection in Disaster Twitter Data. In: Proceedings of the 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019), Valencia, Spain. [WiPe Paper.]
Kropczynski, J., Grace, R., Halse, S., Caragea, D., Caragea, C., Tapia, A. (2019) Refining a Coding Scheme to Identify Actionable Information on Social Media. In: Proceedings of the 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019), Valencia, Spain. [WiPe Paper.]
Ray Chowdhury, J., Caragea, C. and Caragea, D. (2019) Keyphrase Extraction from Disaster-related Tweets, Proceedings of the World Wide Web Conference (WWW'19), 1555-1566, San Francisco, CA. [Regular paper]
Li, X., Zhang, H., Caragea, D. and Imran, M. (2018) Localizing and Quantifying Damage in Social Media Images, In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'18), Barcelona, Spain.
Li, H., Li, X., Caragea, D. and Caragea, C. (2018) Comparison of Word Embeddings and Sentence Encodings as Generalized Representations for Crisis Tweet Classification Tasks, In Proceedings of the ISCRAM Asian Pacific 2018 Conference – Wellington, New Zealand, November 2018.
Mazloom, R., Li, H., Caragea, D., Imran, M., and Caragea, C. (2018). Classification of Twitter Disaster Data Using a Hybrid Feature-Instance Adaptation Approach. In: Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2018), Rochester, NY. [WiPe paper.]
Neppalli, V.K., Caragea, C., and Caragea, D. (2018). Deep Neural Networks versus Naive Bayes Classifiers for Identifying Informative Tweets during Disasters. In: Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2018), Rochester, NY. [WiPe paper.]
Sopova, O., Li, H., and Caragea, D. (2017). Comparison of Two Domain Adaptation Approaches for Classifying Disaster-related Twitter Data In: Proceedings of The 4th International Symposium on Social Networks Analysis, Management and Security (SNAMS 2017), part of the Proceedings of the IEEE International Conference on Future Internet of Things and Cloud (FiCloud-2017), Prague, Czech Republic, 2017. [Acceptance rate: N/A]
Li, H., Caragea, D. and Caragea, C. (2017). Towards Practical Usage of Domain Adaptation Algorithms in Classifying Disaster Related Tweets. In: Proceedings of the 14th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2017), Albi, France, 2017. [WiPe paper. Acceptance rate 68%]
Stanescu, A., Tangirala, K. and Caragea, D. (2016). Study of transductive learning and unsupervised feature construction methods for biological sequence classification. Best Paper Award. In: Proceedings of the International Symposium on Network Enabled Health Informatics, Biomedicine and Bioinformatics, part of the Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016) San Francisco, CA [Regular paper. Acceptance rate 30%]
Neppalli, K., Cerqueira Medeiros, M., Caragea, C., Caragea, D., Tapia, A., Halse, S. (2016). Retweetability Analysis and Prediction during Hurricane Sandy. In: Proceedings of the 13th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2016), Brazil. [Regular paper.]
Herndon, N. and Caragea, D., (2016). Ab initio Splice Site Prediction with Simple Domain Adaptation Classifiers. In: Proceedings of the 7th International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2016), Rome, Italy. [Short paper.]
Roy, S., DeLoach, J., Li, Y., Herndon, N., Caragea, D., Ou, X., Ranganath, V. P., Li, H., and Guevara, N. (2015). Experimental Study with Real-world Data for Android App Security Analysis using Machine Learning. In: Proceedings of the 2015 Annual Computer Security Applications Conference (ACSAC 2015),pages 81-90, Los Angeles, CA [Regular paper. Acceptance rate: 25%].
Stanescu, A., and Caragea, D. (2015). Predicting Cassette Exons Using Transductive Learning Approaches. In: Proceedings of the Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2015),pages 495-502, Niagara Falls, Canada [Regular paper].
Herndon, N., and Caragea, D. (2015). An Evaluation of Self-training Styles for Domain Adaptation on the Task of Splice Site Prediction Best Paper Award. In: Proceedings of the International Symposium on Network Enabled Health Informatics, Biomedicine and Bioinformatics (HI-BI-BI 2015), part of the Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015), pages 1042-1047, Paris, France [Regular paper. Acceptance rate: 35%].
Parimi, R. and Caragea, D. (2015). How to Choose a Recommender System: Insights and Experiences for Large-scale User Personalization. In: Proceedings of the 4th IEEE International Congress on Big Data, Application Track. (IEEE BigData Congress 2015),, pages 475-482, New York, USA, June 27-July 2 [Regular paper. Acceptance rate: N/A].
Parimi, R. and Caragea, D. (2015). Cross-Domain Matrix Factorization for Multiple Implicit-Feedback Domains. In: Proceedings of the International Workshop on Machine learning, Optimization and big Data (MOD 2015), pages 80-92, Taormina - Sicily, Italy, July 21-24 [Regular paper. Acceptance rate: N/A].
Herndon, N. and Caragea, D. (2015). Domain Adaptation with Logistic Regression for Splice Site Prediction. In: Proceedings of the 11th International Symposium on Bioinformatics Research and Application (ISBRA 2015),, pages 125-137, Norfolk, Virginia, June 7-10 [Regular paper. Acceptance rate: 35%].
Tangirala, K., Herndon, N. and Caragea, D. (2015). Community Detection-based Feature Construction for Protein Sequence Classification. In: Proceedings of the 11th International Symposium on Bioinformatics Research and Application (ISBRA 2015),, pages 331-342, Norfolk, Virginia, June 7-10 [Regular paper. Acceptance rate: 35%].
Li, H., Guevara, N., Herndon, N. Caragea, D., Neppalli, K., Caragea, C., Squicciarini, A. and Tapia, A. (2015). Twitter Mining for Disaster Response: A Domain Adaptation Approach. In: 12th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2015), Norway [Short paper. Acceptance rate: 70%].
Stanescu, A., and Caragea, D. (2014). Ensemble-based semi-supervised learning approaches for imbalanced splice site datasets. In: Proceedings of the International Conference on Bioinformatics and Biomedicine (BIBM 2014), Belfast, UK [Regular paper. Acceptance rate: 19%].
Herndon, N., Tangirala, K., and Caragea, D. (2014). Predicting Protein Localization Using a Domain Adaptation Naive Bayes Classifier with Burrows Wheeler Transform Features. In: Proceedings of the International Conference on Bioinformatics and Biomedicine (BIBM 2014), Belfast, UK [Short paper. Acceptance rate: 38%].
Tangirala, K. and Caragea, D. (2014). Community Detection-based Features for Sequence Classiﬁcation. In: Proceedings of the 5th ACM Conference on Bioinformatics and Computational Biology (ACM-BCB 2014), Newport Beach, CA. [Short paper. Acceptance rate: N/A].
Herndon, N., and Caragea, D. (2014). Empirical study of domain adaptation with naive Bayes on the task of splice site prediction . In: Proceedings of the 5th International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2014), Loire Valley, France. [Regular paper. Acceptance rate: 14%]. Nominated for best paper award.
Tangirala, K., and Caragea, D. (2014). Generating Features Using Burrows Wheeler Transformation for Biological Sequences. In: Proceedings of the 5th International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2014), Loire Valley, France. [Short paper. Acceptance rate: 34%].
Tangirala, K., and Caragea, D. (2014). Semi-supervised Classification of Protein Sequences Using Burrows Wheeler Transformation-based Features. In: Proceedings of the 5th International Conference on Bioinformatics and Computational Biology (BICoB 2014 ), Las Vegas, Nevada [Acceptance rate: N/A].
Stanescu, A., and Caragea, D. (2014). Semi-supervised Self-training Approaches for Imbalanced Splice Site Datasets. In: Proceedings of the 5th International Conference on Bioinformatics and Computational Biology (BICoB 2014 ), Las Vegas, Nevada [Acceptance rate: N/A].
Zomlot, L., Chandran, S., Caragea, D., and Ou, X. (2013). Aiding Intrusion Analysis Using Machine Learning. In: Proceedings of the 12th International Conference on Machine Learning and Applications (ICMLA 2013), Special Session on Machine Learning Challenges in Cyber Security Applications, Miami, FL. [Acceptance rate for conference: 26%; for special session N/A].
Stanescu, A., Nagar, S. and Caragea, D. (2013). A Hybrid Recommender System: User Profiling from Keywords and Ratings. In: Proceedings of the 2013 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2013), Atlanta, GA [Regular paper. Acceptance rate: 25%].
Parimi, R., Caragea, D. and Wunderlich, D. (2013). Economic Development through Business Profiling: A Text Analysis based Approach. In: Proceedings of the 2013 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2013), Atlanta, GA [Short paper. Acceptance rate: 53%].
Cheeti, S., Stanescu, A. and Caragea, D. (2013). Cross-Domain Sentiment Classification Using an Adapted Naive Bayes Approach and Features Derived From Syntax Trees. In: Proceeding of the 5th International Conference on Knowledge Discovery and Information Retrieval (KDIR 2013), Vilamoura, Algarve, Portugal [Short paper. Acceptance rate: 30%].
Tangirala, K. and Caragea, D. (2013). Extraction of Gene Regulatory Networks from Biological Literature. In: Proceeding of the IEEE 3rd International Conference on Computational Advances in Bio and medical Sciences (ICCABS 2013), New Orleans, LA [Acceptance rate: 43%].
Parimi, R. and Caragea, D. (2013). Pre-release Box-Office Success Prediction for Motion Pictures. In: Proceeding of the 10th International Conference on Machine Learning and Data Mining (MLDM 2013), p. 571-585, New York, NY [Acceptance rate: 33%]. Nominated for best paper award.
Herndon, N., and Caragea, D. (2013). Naive Bayes Domain Adaptation for Biological Sequences. In: Proceedings of the 4th International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2013), Barcelona, Spain [Regular paper. Acceptance rate: 10%]. Nominated for best student paper award.
Stanescu, A., and Caragea, D. (2012). Semi-Supervised Learning of Alternatively Spliced Exons Using Expectation Maximization Type Approaches. In: Proceedings of the 3rd International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2012), Algarve, Portugal [Short paper. Acceptance rate: 37%].
Tangirala, K., and Caragea, D. (2011). Semi-Supervised Learning of Alternatively Spliced Exons Using Co-Training. In: Proceedings of the International Conference on Bioinformatics and Biomedicine (BIBM 2011), Atlanta, GA [Short paper. Acceptance rate: 39.13%].
Caragea, C., Silvescu, A., Kataria, S. Caragea, D. and Mitra, P. (2011). Classifying Scientific Publications Using Abstract Features. In: Proceedings of the Ninth Symposium on Abstraction, Reformulation, and Approximation (SARA 2011), Parador de Cardona, Cardona, Catalonia, Spain.
Zhang, S., Caragea, D. and Ou, X. (2011). An Empirical Study of Using the National Vulnerability Database to Predict Software Vulnerabilities. In: Proceedings of the 22nd International Conference on Database and Expert Systems Applications (DEXA 2011), Toulouse, France [Regular paper. Acceptance rate: 25%].
Parimi, R. and Caragea, D. (2011). Predicting Friendship Links in Social Net- works Using a Topic Modeling Approach. In: Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2011), Shenzhen, China [Regular paper. Acceptance rate: 9.7%].
Caragea, C., Silvescu, A., Caragea, D. and Honavar, V. (2010). Abstraction-Augmented Markov Models. In: Proceedings of the IEEE Conference on Data Mining (ICDM 2010). Sydney, Australia. [Regular paper. Acceptance rate: 9%].
Caragea, C., Silvescu, A., Caragea, D., and Honavar, V. (2010). Semi-Supervised Sequence Classification Using Abstraction Augmented Markov Models. In: Proceedings of the ACM Conference on Bioinformatics and Computational Biology. Niagara Falls, NY. [Regular paper. Acceptance rate: 28%]
Volkova, S., Caragea, D., Hsu, W.H., Drouhard, J. and Fowles, L. (2010). Boosting Biomedical Entity Extraction by using Syntactic Patterns for Semantic Relation Discovery. In: Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI'10), Toronto, Canada. [Regular paper. Acceptance rate: 16.6%]
Xia, J., Caragea, D. and Hsu, W. (2009). Multi Relational Network Analysis Using a Fast Random Walk with Restart. In: Proceedings of the IEEE International Conference on Data Mining (ICDM 2009), Miami, FL. [Short paper. Acceptance rate: 18%]
Caragea, C., Caragea, D. and Honavar, V. (2009). Learning Link-Based Classifiers from Ontology-Extended Textual Data. In: Proceedings of the 21st International Conference on Tools with Artificial Intelligence (ICTAI 2009), New Jersey. [Regular paper.]
Haridas, M. and Caragea, D. (2009) Exploring Wikipedia and DMoz as Knowledge Bases for Engineering a User Interests Hierarchy for Social Network Applications. In: Proceedings of the 8th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2009), Algarve, Portugal. [Short paper. Acceptance rate: 38%]
Caragea, C., Caragea, D. and Honavar, V. (2009). Learning Link-Based Naive Bayes Classifiers from Ontology-Extended Distributed Data. In: Proceedings of the 8th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2009), Algarve, Portugal. [Short paper. Acceptance rate: 38%]
Kulkarni, S. and Caragea, D. (2009). Towards Bridging the Web and the Semantic Web. In: Proceedings of the 2009 IEEE/WIC/ACM International Conference on Web Intelligence (WI'09), Milan, Italy. [Regular paper. Acceptance rate: 16%]
Kulkarni, S. and Caragea, D. (2009). Computation of the Semantic Relatedness between Words Using Concept Clouds. In: Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (KDIR), part of the International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K). Madeira, Portugal.[Short paper. Acceptance rate: 34%]
Caragea, D., Bahirwani V., Aljandal, W. and Hsu, W. (2009). Ontology-Based Link Prediction in the LiveJournal Social Network. In: Proceedings of the Eight Symposium on Abstraction, Reformulation and Approximation (SARA'09), Lake Arrowhead, CA.
Aljandal, W., Bahirwani, V., Caragea, D. and Hsu, H.W. (2009). Ontology-Aware Classification and Association Rule Mining for Interest and Link Prediction in Social Networks. In: Proceedings of the AAAI 2009 Spring Symposium on Social Semantic Web: Where Web 2.0 Meets Web 3.0, Stanford, CA, March 23-25.
Xia, J., Caragea, D. and Brown, S.J. (2008). Exploring Alternative Splicing Features using Support Vector Machines. In: Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM’08), Philadelphia, PA. [Regular Paper. Acceptance rate: 24%]
Koul, N., Bahirwani, V., Caragea, C., Caragea, D., and Honavar, V. (2008). Learning from Large Autonomous Data Sources using Sufficient Statistics. Short Paper. In: Proceedings of the International Conference on Web Intelligence (WI 2008), Sydney, Australia. [Short Paper. Acceptance rate: 39%]
Harmon, S., DeLoach, S., Robby, Caragea, D. (2008). Leveraging Organizational Guidance Policies with Learning to Self-Tune Multiagent Systems. In: Proceedings of the Second IEEE International Conference on Self-Adaption and Self-Organization (SASO’08). Venice, Italy. [Regular Paper. Acceptance rate: 27%]
Aljandal, W.A., Bahirwani, V., Caragea, D., Hsu, W.H. and Weninger, T. (2008). Validation-based normalization and selection of interestingness measures for association rules. In: Proceedings of ANNIE 2008.
Paradesi, M.S.R., Caragea, D., and Hsu, W.H. (2007). Structural Prediction of Protein-Protein Interactions in Saccharomyces cerevisiae. In: Proceedings of the 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering (BIBE'07). Boston, MA. [Short Paper]
Bao, J., Caragea, D., and Honavar, V. (2006). A Tableau-based Federated Reasoning Algorithm for Modular Ontologies. In: Proceedings of the 2006 IEEE / WIC / ACM International Conference on Web Intelligence. pp. 404-410. Hong Kong. [Acceptance rate: 18%]
Bao, J., Caragea, D., and Honavar, V. (2006). On the Semantics of Linking and Importing in Modular Ontologies. In: Proceedings of the International Semantic Web Conference (ISWC 2006). I. Cruz et al. (Eds.) LNCS 4273, pages 72-86. Athens, Georgia, USA. [Acceptance rate: 23%]
Caragea, D., Zhang, J., Pathak, J., and Honavar, V. (2006). Learning Classifiers from Distributed, Ontology-Extended Data Sources. In: Proceedings of the 8th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2006). Krakov, Poland. Lecture Notes in Computer Science. Berlin: Springer. [Acceptance rate: 35%]
Bao, J., Caragea, D., and Honavar, V. (2006). Modular Ontologies - A Formal Investigation of Semantics and Expressivity. Best Paper Award. In: Proceedings of the First Asian Semantic Web Conference (ASWC 2006). September 2-7, 2006, Beijing, China. R. Mizoguchi, Z. Shi, and F. Giunchiglia (Eds.) LNCS 4185, pp. 616–631, Springer-Verlag. [Acceptance rate: 18%]
Wickham, H., Caragea, D. and Cook, D. (2006). Exploring High-Dimensional Classification Boundaries. In: Proceedings of the 38^th Symposium on the Interface of Statistics, Computing Science, and Applications - Interface 2006: Massive Data Sets and Streams. May 24-27, 2006, Pasadena, CA, USA.
Bao, J., Caragea, D., and Honavar, V. (2006) Towards Collaborative Environments for Ontology Construction and Sharing. In: Proceedings of the 2006 International Symposium on Collaborative Technologies and Systems (CTS 2006). May 14-17, 2006 Las Vegas, Nevada, USA.
Caragea, D., Zhang, J., Bao, J., Pathak, J., and Honavar, V. (2005). Invited Paper. Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous Information Sources (Invited paper). In: Proceedings of the 16th International Conference on Algorithmic Learning Theory (ALT 2005). Lecture Notes in Computer Science. Singapore. Vol. 3734, pp. 13-44. Berlin: Springer-Verlag.
Zhang, J., Caragea, D., and Honavar, V. (2005). Learning Ontology-Aware Classifiers. In: Proceedings of the Eight International Conference on Discovery Science (DS 2005), Springer-Verlag Lecture Notes in Computer Science. October 8-11, 2005, Singapore. Vol. 3735, pp. 308-321. Berlin: Springer-Verlag. [Acceptance rate: 21%].
Caragea, D., Pathak, J., and Honavar, V. (2004). Learning Classifiers from Semantically Heterogeneous Data. In: Proceedings of the Third International Conference on Ontologies, DataBases and Applications of Semantics for Large Scale Information Systems (ODBASE 2004), Springer-Verlag Lecture Notes in Computer Science. October 25-29, 2004, Agia Napa, Cyprus. LNCS #3291, pp. 963-980. Springer-Verlag. [Acceptance rate: 25%]
Cook, D., Caragea, D., and Honavar, V. (2004). Visualization for Classification Problems, with Examples Using Support Vector Machines. In: Proceedings of Computational Statistics (COMPSTAT 2004), 16th Symposium of IASC, August 23-27, 2004, Prague, Czech Republic. Pp. 799-806. Springer-Verlag.
Caragea, D., Cook, D. and Honavar, V. (2003). Towards Simple, Easy-to-Understand, but Accurate Classifiers. In: Proceedings of the Third IEEE International Conference on Data Mining (ICDM 2003), November 19-22, 2003, Melbourne, FL, USA. Pp. 497-500. IEEE Press. [Acceptance rate: 23%]
Reinoso J., Silvescu, A., Caragea, D., Pathak, J., and Honavar, V. (2003). A Federated Query-Centric Approach to Information Extraction and Integration from Heterogeneous, Distributed and Autonomous Data Sources. In: Proceedings of the 2003 IEEE International Conference on Information Reuse and Integration (IRI 2003), October 27-29, 2003, Las Vegas, NV, USA. Pp. 183-191. IEEE Press.
Caragea, D., Silvescu, A., and Honavar, V. (2003). Decision Tree Induction from Distributed Data Sources. In: Proceedings of the Conference on Intelligent Systems Design and Applications (ICDA 2003), August 10-13, 2004, Tulsa, OK, USA. Pp. 341-350. Springer-Verlag.
Caragea, D., Cook, D., and Honavar, V. (2001). Gaining Insights into Support Vector Machine Classifiers Using Projection-Based Tour Methods. In: Proceedings of the Conference on Knowledge Discovery and Data Mining (KDD 2001), August 26-29, San Francisco, CA, USA. Pp. 251-256. ACM Press. [Acceptance rate: 25%]
Agapie, A. and Caragea, D. (1997). Genetic Algorithms, Schemata Construction and Statistics. In: Proceedings of the International Conference on Computational Intelligence, Theory and Applications, 5th Fuzzy Days, Dortmund, Germany. Pp. 16-23.

Refereed Workshop Papers

DeLoach, J., and Caragea, D. (2017). Twitter-Enhanced Android Malware Detection. In: Proceedings of the 2017 International Workshop on Big Data Analytics for Cyber Intelligence and Defense (BDA4CID 2017), in conjunction with the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), Boston, MA.
DeLoach, J., Caragea, D., Ou, Xinming (2016). Android Malware Detection with Weak Ground Truth Data. In: Proceedings of the 3rd International Workshop on Pattern Mining and Application of Big Data (BigPMA). In conjunction with the 2016 IEEE International Conference on Big Data (IEEE BigData 2016). Washington D.C., USA, 2016. [Regular paper. Acceptance rate: N/A]
Li, Y., Sundaramurthy, S.C., Bardas, A.G., Ou,X. Caragea, D., Hu, X. and Jang, J. (2015). Experimental Study of Fuzzy Hashing in Malware Clustering Analysis. In: Proceedings of the 8th Workshop on Cyber Security Experimentation and Test, Usenix (CSET-15), Washington D.C.
Parimi, R., and Caragea, D. (2015). Leveraging Multiple Networks for Author Personalization. In: Proceedings of the AAAI-15 Workshop on Scholarly Big Data: AI Perspectives, Challenges, and Ideas (AAAI-15 SBD), Austin, Texas [Acceptance rate: 21%].
Parimi, R., and Caragea, D. (2014). Community Detection on Large Graph Datasets for Recommender Systems. In: Proceedings of the ICDM-2014 Workshop on Data Mining in Networks (DaMNet 2014), Shenzhen, China. [Acceptance rate: 40%].
Volkova, S., Caragea, D., Hsu, W., Bujuru, S. (2010). Animal Disease Event Recognition and Classification. In: Proceedings of the First International Workshop on Web Science and Information Exchange in the Medical Web (MedEx'10). Collocated with the 19th World Wide Web Conference WWW-2010, Raleigh, NC, USA.
Caragea, C., Silvescu, A., Caragea, D. and Honavar, V. (2009). Abstraction Augmented Markov Models. In: Proceedings of the NIPS Workshop on Machine Learning in Computational Biology (MLCB). [Acceptance rate: 30%]
Bahirwani, V., Caragea, D., Aljandal, W. and Hsu, H.W. (2008). Ontology Engineering and Feature Construction for Predicting Friendship Links in the Live Journal Social Network. In: Proceedings of the KDD 2008 Second Workshop on Social Network Mining and Analysis (SNA-KDD). Las Vegas, NV, August 2008. ACM Digital Library. [Regular paper. Acceptance rate: 35%]
Bao, J., Caragea, D. and Honavar, V. (2007). Query Translation for Ontology-Extended Data Sources. In: Proceedings of the AAAI 2007 Workshop on Semantic e-Science, Vancouver, Canada. [Acceptance rate: 33%]
Caragea, D., Bao, J. and Honavar, V. (2007). Learning Relational Bayesian Classifiers on the Semantic Web. In: Proceedings of the IJCAI 2007 Workshop on Semantic Web for Collaborative Knowledge Acquisition (SWeCKa 2007). In conjunction with the Twentieth International Joint Conference on Artificial Intelligence, Hyderabad, India, January 2007.
Bao, J., Hu, Z., Caragea, D., Reecy, J., and Honavar, V. (2006). A Tool for Collaborative Construction of Large Biological Ontologies. In: Fourth International Workshop on Biological Data Management (BIDM 2006), pp. 191-195. Krakov, Poland. IEEE Press
Bao, J., Caragea, D., and Honavar, V. (2006). A Distributed Tableau Algorithm for Package-based Description LogicsOntolo. In: Proceedings of the Second International Workshop on Context Representation and Reasoning (CRR 2006). Riva del Garda, Italy. CEUR.
Pathak, J., Koul, N., Caragea, D. and Honavar, V. (2005). A Framework for Semantic Web Services Discovery. In: Proceedings of the 7th ACM International Workshop on Web Information and Data Management (WIDM-2005), Bremen, Germany. Pp. 45-50. ACM press. [Acceptance rate: 27%]
Caragea, D., Pathak, J., Bao, J., Silvescu, A., Andorf., C., Dobbs, D., and Honavar, V. (2005). Information Integration from Semantically Heterogeneous Biological Data Sources. In: Proceedings of the 3rd International Workshop on Biological Data Management (BIDM 2005), DEXA Workshops 2005, Copenhagen, Denmark. Pp. 580-584. IEEE Computer Society.
Caragea, D., Pathak, J., Bao, J., Silvescu, A., Andorf., C., Dobbs, D. and Honavar, V. (2005). Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Sources. In: Proceedings of the 2nd International Workshop on Data Integration in Life Sciences (DILS 2005), San Diego, CA. Vol. 3615, pp. 175-190. Berlin: Springer-Verlag. [Acceptance rate: 35%]
Pathak, J., Caragea, D. and Honavar, V. (2004). Ontology Extended Component-Based Workflows: A Framework for Constructing Complex Workflows from Semantically Heterogeneous Software Components. In: Proceedings of the VLDB-04 Second International Workshop on Semantic Web and Databases (SWDB 2004), August 29 – September 3, 2004, Toronto, Canada. Vol. 3372, pp. 41-56. Springer-Verlag.
Caragea, D., Reinoso, J., Silvescu, A. and Honavar, V. (2003). Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources. In: Proceedings of the IJCAI International Workshop on Information Integration on the Web (IIWeb 2003). August 9-15, 2003, Acapulco, Mexico. Pp. 99-104.
Caragea, D., Silvescu, A., and Honavar, V. (2000). Agents that Learn from Distributed Dynamic Data Sources. In: Proceedings of the Workshop on Learning Agents, Agents 2000/ECML 2000. Stone, P. and Sen, S. (Eds.) June 3, Barcelona, Spain.
Caragea, D., Silvescu, A., and Honavar, V. (2000). Towards a Theoretical Framework for Analysis and Synthesis of Distributed and Incremental Learning Agents. In: Proceedings of the Workshop on Distributed and Parallel Knowledge Discovery. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2000) August 20, Boston, MA, USA.

Refereed Extended Abstracts

Alfs, E., Caragea, D., Albin, N., Poggi-Corradini, P. (2019) Identifying Android Malware Using Network-based Approaches. In: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, Honolulu, Hawaii. [Student poster program.]
DeLoach, J., and Caragea, D. (2017). Using Twitter Data to Improve Android Malware Detection. In: 2017 Annual Computer Security Applications Conference (ACSAC-2017). Poster program. Orlando, FL, USA, 2017
Li, Y., Ekambaram, R., DeLoach, J., Wei, F., Hall, L., Ou, X. and Caragea, D. (2017). Zero-Day Android Malware Detection Using Machine Learning. In: 2017 Annual Computer Security Applications Conference (ACSAC-2017). Poster program. Orlando, FL, USA, 2017
DeLoach, J., Caragea, D., Ou, Xinming (2017). Android Malware Detection with Weak Ground Truth Data. Proceedings of the AAAI-17 Student Abstract and Poster Program, AAAI 2017 (Poster presentation.)
Bahirwani, V. and Caragea, D. (2011). Study on Regulatory Motifs in Arabidopsis thaliana. In: Proceedings of the 2nd ACM Conference on Bioinformatics and Computational Biology (ACM-BCB'11), Poster program. Chicago, IL.
Elshamy, W., Caragea, D. and Hsu, W.H. (2010). KSU KDD: Word Sense Induction by Clustering in Topic Space. In: Proceedings of the SemEval wokshop. Poster program. Collocated with the 48th Annual Meeting of the Association for Computational Linguistic (ACL'10), Uppsala.
Bahirwani, V. and Caragea, D. (2009). Exploring Transcription Patterns in Arabidopsis thaliana. In: Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (RECOMB'09), Poster Program. Tucson, AZ.
Paradesi, M.S.R., Caragea, D., and Hsu, W.H. (2007). Structural Prediction of Protein-Protein Interactions in Saccharomyces cerevisiae. In: Proceedings of the Annual Meeting of the International Society for Computational Biology (ISMB 2007), Poster Program, Vienna, Austria.
Bao, J., Caragea, D., and Honavar, V. (2006). Package-based Description Logics - Preliminary Results. In: International Semantic Web Conference - Doctoral Consortium (ISWC-DC 2006). Athens, Georgia, USA. Slides. [Acceptance rate: 26%]
Caragea, D. and Honavar, V. (2006). Knowledge Discovery from Disparate Earth Data Sources. Second NASA Data Mining Workshop: Issues and Applications in Earth Sciences. Poster Session. Pasadena, CA, May 23-24, 2006.
Caragea, D., Bao, J., Pathak, J. and Honavar, V. (2005). Ontology-based Information Integration using INDUS System. In: The Program of the Eight Annual Bio-Ontologies Meeting (Bio-Ont SIG 2005). Poster Session. Detroit, Michigan.
Caragea, D., Silvescu, A., Pathak, J., Bao, J., Andorf., C., Yan, C., Dobbs, D. and Honavar, V. (2005). Knowledge Acquisition from Autonomous, Distributed, Semantically Heterogeneous Data Sources. In: Proceedings of the Annual Meeting of the International Society for Computational Biology (ISMB 2005), Poster Program, Detroit, Michigan.
Pathak, J., Bao, J., Caragea, D., Silvescu, A., Andorf., C., Yan, C., Dobbs, D. and Honavar, V. (2005). INDUS: A System for Information Integration and Knowledge Acquisition from Autonomous, Distributed, and Semantically Heterogeneous Data Sources. In: The Program of the Annual Meeting of the International Society for Computational Biology (ISMB 2005), Demo Program, Detroit, Michigan.
Caragea, C., Caragea, D. and Honavar, V. (2005). Learning Support Vector Machine Classifiers from Distributed Data Sources. In: Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI 2005), Student Abstract and Poster Program, Pittsburgh, Pennsylvania. Pp. 1602-1603. AAAI Press.
Caragea, D., Syeda-Mahmood, T. (2004). Semantic API Matching for Automatic Service Composition. In: Proceedings of the 13th International World Wide Web conference on Alternate track papers & posters, Poster session (WWW 2004), May 17-22, 2004, New York, NY, USA. Pp. 436-437. ACM Press.
Caragea, D. (2002). Learning in Open-Ended Dynamic Distributed Environments. In: Proceedings of the 18th National Conference on Artificial Intelligence (AAAI 2002), Doctoral Consortium Program. Edmonton, Alberta, Canada. Pp. 980. AAAI Press.
Caragea, D., Silvescu, A., and Honavar, V. (2000). Incremental and Distributed Learning Using Support Vector Machines. In: Proceedings of the17th National Conference on Artificial Intelligence (AAAI 2000), Student Abstract and Poster Program. Austin, TX. Pp. 1067. AAAI Press.

Technical Reports

Caragea, D., Cook, D., and Honavar, V. (2005). Visual Methods for Examining Support Vector Machine Results, with Applications to Gene Expression Data Analysis. ISU Technical Report, December 2005.
Silvescu A., Caragea D., Atramentov A. (2002). Graph Databases. Technical Report. May 2002. [ slides ]

Tutorials

Honavar, V. and Caragea, D. (2006). Semantic Web Technologies for Collaborative Knowledge Acquisition. In conjunction with the 2006 1^st International Conference on Digital Information Management (ICDIM), December 06-08, 2006, Christ College, Bangalore, India.
Honavar V. and Caragea, D. (2006). Collaborative Knowledge Acquisition on the Semantic Web. In conjunction with the 2006 International Multi-Conference on Computing in the Global Information Technology (ICCGI). August 1-3, 2006, Bucharest, Romania.
Honavar, V. and Caragea, D. (2006). Collaborative Knowledge Acquisition from Semantically Disparate, Distributed Data Sources. In conjunction with the 2006 International Symposium on Collaborative Technologies and Systems (CTS). May 14-17, 2006, Las Vegas, Nevada, USA.

Posters and Presentations

Carolan, J.C.,Caragea, D., Reese, J.C., Reeck, G.R., Mutti, N.S., Tagu, D., Edwards, O.R. and Wilkinson, T.L. (2011) An insight into the salivary secretome of the pea aphid Acyrthosiphon pisum. Sixth International Symposium on Molecular Insect Science, 2-5 October 2011, Amsterdam, The Netherlands.
Stanescu, A., Caragea, D. and Brown, S.J. (2011) Semi-Supervised Learning Approaches for Predicting Alternatively Spliced Exons. Poster presented by A. Stanescu at the CRA-W Grad Cohort Workshop, April 1-2, 2011, Boston, MA.
Volkova, S., Caragea, D. and Hsu, W. (2010) Automated Event Extraction and Named Entity Recognition in the Domain of Veterinary Medicine. Poster presented by S. Volkova at the 2010 Grace Hopper Celebration, September 28 - October 2, Atlanta, GA.
Volkova, S., Hsu, W. and Caragea, D. (2009) Named Entity Annotation and Tagging in the Domain of Epizootics. Poster presented by S. Volkova at the Women in Machine Learning Workshop co-located with NIPS’09 Conference, December 2009, Vancouver, CA.
Narro, M., Ram, S., Caragea, D., Cushing, J. and Brown, S. (2009) Computing Op- portunities in Plant Sciences. Poster presented by M. Narro at the 2009 Grace Hopper Celebration, September 30 - October 3, Tucson, AZ.
Johnson, L., Surabhi, G.C., Kumar, S., Caragea, D., Lu, N., Shah, J. (2008). Chronic and transient effects of nitrogen saturation on root processes in a dominant prairie grass Andropogon gerardii: Linking gene expression profiles and ecological responses. Poster presented at the Plant and Animal Genomics meeting, January 2009, San Diego, CA.
Caragea, D., Kallumadi, S., Dittmer, N., Chellapilla, S., Mutti, N., Feng, C., Pierson, M., Heerman, M., Culbertson, C., Reese, J., Edwards, O. and Reeck, G. (2008) Identifying Specialized Salivary Gland Transcripts in Pea Aphid Using Bioinformatics Tools. Second Annual Arthropod Genomics Symposium: New Insights from Arthropod Genomes, April 11 - 13, 2008, in Kansas City.
Chellapilla, S., Kallumadi, S., Park, Y., Caragea, D. and Brown, S.J. (2008) ArthropodEST: A Pipeline for Automated EST Data Analysis. Second Annual Arthropod Genomics Symposium: New Insights from Arthropod Genomes, April 11 - 13, 2008, in Kansas City.
Cui, F., Dai, H., Hiromasa, Y., Caragea, D., Sheng,C., Reese, J., Edwards, O. and Reeck, G. (2008) Characterization of an endoplasmic reticulum protein from the salivary glands of the pea aphid, Acyrthosiphon pisum. Second Annual Arthropod Genomics Symposium: New Insights from Arthropod Genomes, April 11 - 13, 2008, in Kansas City.
Steller, M., Kambhampati, S., and Caragea, D. (2008) Bioinformatic Analysis of ESTs from Termite Castes. Second Annual Arthropod Genomics Symposium: New Insights from Arthropod Genomes, April 11 - 13, 2008, in Kansas City.
Surabhi, G.C., Kumar, S., Alam, N., Caragea, D., Lu, N., Hurt, A., Johnson, L., Shah, J. (2008) Chronic and transient effects of nitrogen saturation on root processes in a dominant prairie grass Andropogon gerardii: Linking gene expression profiles and ecological responses. Presented at Plant Biology 2008, Mérida, Mexico.
Honavar, V. and Caragea, D. (2006). Querying Semantically Heterogeneous Data Sources from a User’s Point of View. 2006 Semantic Technology Conference. San Jose, CA, March 6-9, 2006.
Caragea, D. (2006). Collaborative Knowledge Acquisition from Distributed, Semantically Heterogeneous Data Sources. Technology Screening Panel, New Ventures AgTech Initiative, Eastern Iowa Community College District, Davenport, IA. February 16, 2006. Invited Talk.
Caragea, D. (2005). Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Sources. Division of Biomedical Informatics at Cincinnati Children's Hospital Medical Center, Cincinnati, OH, October 21^st, 2005. Invited Talk.
Caragea, D. (2004). Learning Classifiers from Distributed, Semantically Heterogeneous, Autonomous Data Sources. Multimedia and Database Research Group, Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, November 5th 2004.
Caragea, D. and Honavar, V. (2004). Knowledge Acquisition from Semantically Heterogeneous Distributed Data. Demo Presentation at The NSF Information and Data Management Workshop (IDM 2004), Cambridge, Massachusetts, October 10-12, 2004.
Caragea, D. (2004). Learning Classifiers from Distributed, Semantically Heterogeneous, Autonomous Data Sources. The IBM Data Analytics Research Group, T.J. Watson Research Center, Yorktown Heights, NY, October 4^th, 2004.
Caragea, D. (2004). Learning Classifiers from Distributed, Semantically Heterogeneous, Autonomous Data Sources. Colloquium Series Spring 2004, Department of Computer Science, Iowa State University, Ames, IA, July 27^th, 2004.
Jie, B., Yan, C., Caragea, D. and Honavar, V. (2004) Integration of Ontology-Extended Biological Data Sources. Poster presented at Standards and Ontologies for Functional Genomics (SOFG 2004), Philadelphia, PA, October 23-26, 2004.
Caragea, D., Silvescu, A., and Honavar, V. (2000). Multi-Agent Learning from Distributed Data Sources.Workshop on Multi-Agent learning: Theory and Practice, organized by Gerry Tesauro and Amy Greenwald. International Conference on Machine Learning (ICML 2000), Stanford University.