Research in Artificial Intelligence

Synopsis of the Research Area

Artificial intelligence studies how computers can solve problems that seem to require intelligence when performed by people. As one prominent researcher puts it: "AI is the attempt to answer the question: Why are computers so stupid?"AI has many specialized sub-fields. Central problems in the field are problems such as representing knowledge, implementing reasoning methods, learning from experience, understanding and generated language, the interpretation of perceptions, and interacting with the world. CDM has a number of faculty members with AI-related research. Computer vision and data mining can be considered sub-fields of AI, but are listed separately on these research pages

Recent Publications

Robin Burke

Research areas: Recommender systems, social computing.

Students:

  • Fatemeh Vahedian

Sample Publications:

  • Burke, R. Evaluating the Dynamic Properties of Recommendation Algorithms. In Proceedings of the 4th ACM International Conference on Recommender Systems (Recsys ’10), pp. 225-228. Barcelona, Spain. September 2010.
  • Burke, R. & Ramezani, M. (2010) Matching Recommendation Domains and Technologes. In Kantor, P., Ricci, F., Rokach, L. & Shapira, B. eds. Handbook of Recommender Systems. Springer.
  • Burke, R.; Hurley, N. & O'Mahoney, M. (2010) Robust Collaborative Recommenders. In Kantor, P., Ricci, F., Rokach, L. & Shapira, B. eds. Handbook of Recommender Systems. Springer.
  • Mobasher, B.; Burke, R.; Bhaumik, R. & Williams, C. (2007) Towards Trustworthy Recommender Systems: An Analysis of Attack Models and Algorithms. ACM Transactions on Internet Technology. 7(4), article 23 (38 pages). 2007.

For more information, see http://josquin.cs.depaul.edu/~rburke/


Peter Hastings

Research areas: Intelligent tutoring systems, serious games, natural language processing

Students:

  • Simon Hughes: Automatically inferring causal structure in student essays using Machine Learning and Natural Language Processing
  • Ali Alkhafaji: Critical analysis of the role of mystery in videogames
  • Daneih Ismail: Technology-supported learning

Sample Publications:

  • Machine Learning and Natural Language Processing
    • Hastings, P., Hughes, S., Britt, M.A., Wallace, P., and Blaum, D. (in press). Stratified learning for reducing training set size. In ITS 2016, LNCS 9684, Springer, Berlin.
    • Hughes, S., Hastings, P., Britt, M.A., Wallace, P., and Blaum, D. (2015). Machine Learning for Holistic Evaluation of Scientific Essays. In Proceedings of Artificial Intelligence in Education 2015, Springer, Berlin.
  • Serious Games
    • Alkhafaji, A., Grey, B., and Hastings, P. (2013). Perception vs. Reality: Challenge, Control and Mystery in Video Games. In Proceedings of CHI 2013 Games User Research Workshop.
    • Alkhafaji, A., Grey, B., and Hastings, P. (2013). A New Design And Analysis Methodology Based On Player Experience. In Proceedings of CHI 2013 Games User Research Workshop.
  • Cognitive Science
    • M.A. Britt, Kopp, K., Durik, A., Blaum, D., and Hastings, P. (in press). Identifying General Cognitive Abilities Involved in Argument Comprehension and Evaluation. German Journal of Educational Psychology, 30(2-3):1–17.
    • Costello, J. and Hastings, P. (2013). Evolution of Response Time Distribution in Menu Search. In Proceedings of ICCM 2013: 12th International Conference on Cognitive Modelling.

For more information, see http://reed.cs.depaul.edu/peterh/.


Steve Lytinen

Research areas and selected publications:


Bamshad Mobasher

Research areas: data mining, recommender systems, social computing

Students:

  • Jonathan Gemmel, Thomas Schimoler: Hybrid recommendation in social tagging applications
  • Ahu Sieg: Personalization using ontological user profiles
  • Runa Bhaumik: Vulnerabilities of user-adaptive systems
  • Laura Christiansen: Temporal evolution of social tagging systems.

Sample Publications:

  • Castro-Herrera, C.; Duan, C.;  Cleland-Huang, J. & Mobasher, B. (2009) A Recommender System for Requirements Elicitation in Large-Scale Software Projects. Proceedings of the 24th Annual ACM Symposium on Applied Computing, Data Mining track, Honolulu, HI.
  • Shepitsen, A.; Gemmell, J.; Mobasher, B. & Burke, R. (2008) Personalized Recommendation in Collaborative Tagging Systems Using Hierarchical Clustering. Proceedings of the 2nd ACM International Conference on Recommender Systems (RecSys'08), Lausanne, Switzerland.
  • Duan, C.; Cleland-Huang, J. & Mobasher, B.  (2008) A Consensus Based Approach to Constrained Clustering of Software Requirements. Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM'08) , Napa, CA.
  • Gemmell, J.; Shepitsen, A.; Mobasher, B. & Burke, R. (2008) Personalizing Navigation in Folksonomies Using Hierarchical Tag Clustering. Proceedings of the 10th International Conference on Data Warehousing and Knowledge Discovery (DaWaK'08), Turin, Italy, September, 2008. Lecture Notes in Computer Science 5182, pp. 196-205, Springer.

For more information, see http://maya.cs.depaul.edu


Noriko Tomuro

Research Interests: Natural language processing and machine learning.

Students:

  • Julie Zhang: Information Extraction from biomedical texts
  • Andriy Shepitsen: Use of NLP in Games Research
  • Emilia Apostolova: Lexical semantics

Sample Publications:

  • Zagal, J., Tomuro, N. and Shepitsen, A. (2010). "Natural Language Processing for Games Studies Research". Games Research Methods seminar, http://gamesmethods.wordpress.com
  • Apostolova, E., Neilan, S., An, G., Tomuro, N. and Lytinen, S. (2010). "Djangology: A Light-weight Web-based Tool for Distributed Collaborative Text Annotation". Accepted at the 7th International Conference on Language Resources and Evaluation (LREC 2010).
  • Zhang, Y., Tomuro, N., Furst, J. and Raicu, D. (2010). "Image Enhancement and Edge-based Mass Segmentation in Mammogram". In Proceedings of the SPIE Symposium on Medical Imaging (SPIE-2010).
  • Shepitsen, A. and Tomuro, N. (2009). "Search in Social Tagging Systems Using Ontological User Profiles". In Proceedings of the 3rd Int'l AAAI Conference on Weblogs and Social Media (ICWSM 2009).

    For more information, see http://condor.depaul.edu/~ntomuro/research.