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ARDA AQUAINT Computational Implicatures for Advanced Question Answering
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The capability of interpreting question implicatures in advanced Question Answering systems is a very imporant feature. When using a Question Answering system to find information, a professional analyst cannot separate his/her intentions and beliefs from the formulation of the question and therefore (s)he incorporate intentions and beliefs in the interrogation. Moreover, beyond the question, the analyst sometimes makes a proposal or an assertion. This implied information, not recognizable at the syntactic or semantic level, has great importance in the interpretation of a question, and therefore in the quality of the answers returned by a Questions Answering system. This project concerns with the study and development of computational methods that enable coercions of implicatures in the context of advanced Question Answering. This project is sponsored by ARDA.
PI: Dr. Sanda Harabagiu
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ARP: Knowledge Mining for Open-Domain Information Extraction
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Nowadays, access to information from large-scale on-line text collections is largely limited to keyword-based searches which retrieve entire documents or passages containing the query keywords. While such tools are often satisfactory for retrieving information on general topics, they provide little support for accessing information involving specific relationships, events or facts.
The Information Extraction (IE) technology enables the generation of structured, tabular representations of selected relations from large text collections - representations which can support more detailed document querying. However, IE systems rely on domain knowledge, thus imposing customization every time when a new topic is considered. This explains why until now, developing extraction systems for a broad range of relations, spanning a large number of semantic domains has been too expensive and time-consuming. This research concerns with the development of the infrastucture that enables open-domain IE. This research is sponsored by the Advanced Research Program of the Texas Higher Education Coordinating Board.
PI: Dr. Sanda Harabagiu
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ATP: Text Mining for Telecommunications
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The text mining technology aims to discover new knowledge from unrestricted textual documents. In this project we build a text mining technology and apply it to the telecommunications industry. This includes the development of knowledge bases and ontologies by processing documents relevant to telecommunications. This research is sponsored by the Advanced Research Program of the Texas Higher Education Coordinating Board.
PI: Dr. Dan Moldovan
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