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Semantic Software Lab
Concordia University
Montréal, Canada

Text Mining

Combining Biological Databases and Text Mining to support New Bioinformatics Applications

Witte, R., and C. J. O. Baker, "Combining Biological Databases and Text Mining to support New Bioinformatics Applications", Natural Language Processing and Information Systems: 10th International Conference on Applications of Natural Language to Information Systems (NLDB 2005), vol. 3513, Alicante, Spain : Springer-Verlag, pp. 310–321, June 15–17, 2005.

{Ontological Text Mining of Software Documents}

Witte, R., Q. Li, Y. Zhang, and J. Rilling, "{Ontological Text Mining of Software Documents}", NLDB, vol. 4592, CNAM, Paris, France : Springer, pp. 168–180, June 27–29, 2007.

{Semantic Assistants: SOA for Text Mining}

Witte, R., and N. Papadakis, "{Semantic Assistants: SOA for Text Mining}", CASCON 2009 Technical Showcase, Markham, Ontario, Canada, November 2–9, 2009.

Ontology-Based Extraction and Summarization of Protein Mutation Impact Information

Naderi, N., and R. Witte, "Ontology-Based Extraction and Summarization of Protein Mutation Impact Information", Proceedings of the 2010 Workshop on Biomedical Natural Language Processing (BioNLP 2010), Uppsala, Sweden : Association for Computational Linguistics (ACL), pp. 128--129, July 15, 2010.

The GATE Multi-Parser Predicate-Argument EXtractor Component (MultiPaX)

The GATE Multi-Parser Predicate-Argument EXtractor Component (MultiPaX) can extract predicate-argument structures (PAS) from the output of different parsers.

Semantic Assistants Project

In the Semantic Assistants project, we investigate how to support users in content retrieval, analysis, and development, by offering context-sensitive NLP services directly integrated with common desktop applications (word processors, email clients, Web browsers, ...), web information systems (wikis, portals) and mobile applications (based on Android). They are implemented through an open service-oriented architecture, using Semantic Web ontologies and W3C Web Services.

Fuzzy Believer

The growing number of publicly available information sources makes it impossible for individuals to keep track of all the various opinions on one topic. The goal of our fuzzy believer project is to extract and analyze statements of opinion from newspaper articles.

Beliefs are modeled using a fuzzy-theoretic approach applied after NLP-based information extraction. A fuzzy believer models a human agent, deciding what statements to believe or reject based on different, configurable strategies.

Open Mutation Miner (OMM) Project

In the Open Mutation Miner (OMM) project we investigate the combination of NLP, ontologies, and bioinformatics tools for the extraction and analysis of mutations and their impacts from the bibliome.

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