CCG: Funding

Themes | Projects | Funding | Past Projects

Machine Learning for Security: Digital Guards for Insider Threat Detection

Supported by BOEING

Period: 2005-2006

Relevant Projects:

Digital Guards for Open System Security

Relevant Publications:

D. Roth, M. Sammons, and V. Vydiswaran, A Framework for Entailed Relation Recognition. Proc. of the Annual Meeting of the ACL (2009) [bibitem]
E. Bengtson and D. Roth, Understanding the Value of Features for Coreference Resolution. EMNLP (2008) pp. xx--yy [bibitem]
V. Srikumar, R. Reichart, M. Sammons, A. Rappoport, and D. Roth, Extraction of Entailed Semantic Relations Through Syntax-based Comma Resolution. Proc. of the Annual Meeting of the ACL (2008) [bibitem]
B. Liebald, D. Roth, N. Shah, and V. Srikumar, Proactive Intrusion Detection. Proceedings of the National Conference on Artificial Intelligence (AAAI) (2008) [bibitem]
M. Chang, L. Ratinov, D. Roth, and V. Srikumar, Importance of Semantic Represenation: Dataless Classification. Proceedings of the National Conference on Artificial Intelligence (AAAI) (2008) [bibitem]
M. Chang, L. Ratinov, N. Rizzolo, and D. Roth, Learning and Inference with Constraints. Proceedings of the National Conference on Artificial Intelligence (AAAI) (2008) [bibitem]
D. Roth and M. Sammons, Semantic and Logical Inference Model for Textual Entailment. Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing (2007) pp. 107--112 [bibitem]
M. Chang, L. Ratinov, and D. Roth, Guiding Semi-Supervision with Constraint-Driven Learning. Proc. of the Annual Meeting of the ACL (2007) pp. 280--287 [bibitem]

Focused Textual Entailment

Supported by BOEING

Period:

This project is building a capability for identifying text fragments that exhibit a set of specifiable semantic properties in large text corpora. The objective is to investigate and develop advanced learning and reasoning technologies in support of natural language understanding-related tasks. We will develop an approach to focused textual entailment in the context of text anonymizing. The research is investigating both a novel inference method for focused textual entailment, and methods for acquiring appropriate declarative knowledge required to support this inference. We will apply and evaluate it in the context of anonymizing text snippets with respect to specific goals.

Relevant Projects:

Digital Guards for Open System Security

Relevant Publications:

D. Roth, M. Sammons, and V. Vydiswaran, A Framework for Entailed Relation Recognition. Proc. of the Annual Meeting of the ACL (2009) [bibitem]
E. Bengtson and D. Roth, Understanding the Value of Features for Coreference Resolution. EMNLP (2008) pp. xx--yy [bibitem]
V. Srikumar, R. Reichart, M. Sammons, A. Rappoport, and D. Roth, Extraction of Entailed Semantic Relations Through Syntax-based Comma Resolution. Proc. of the Annual Meeting of the ACL (2008) [bibitem]
B. Liebald, D. Roth, N. Shah, and V. Srikumar, Proactive Intrusion Detection. Proceedings of the National Conference on Artificial Intelligence (AAAI) (2008) [bibitem]
M. Chang, L. Ratinov, D. Roth, and V. Srikumar, Importance of Semantic Represenation: Dataless Classification. Proceedings of the National Conference on Artificial Intelligence (AAAI) (2008) [bibitem]
M. Chang, L. Ratinov, N. Rizzolo, and D. Roth, Learning and Inference with Constraints. Proceedings of the National Conference on Artificial Intelligence (AAAI) (2008) [bibitem]
D. Roth and M. Sammons, Semantic and Logical Inference Model for Textual Entailment. Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing (2007) pp. 107--112 [bibitem]
M. Chang, L. Ratinov, and D. Roth, Guiding Semi-Supervision with Constraint-Driven Learning. Proc. of the Annual Meeting of the ACL (2007) pp. 280--287 [bibitem]