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- FALCON: Boosting Knowledge for Answer Engines
- This paper discusses FALCON. Abstract: This paper presents the features of FALCON, an answer engine that integrates different forms of syntactic, semantic and pragmatic knowledge for the goal of achieving better performance. The answer engine handles question reformulations, finds the expected answer type from a large hierarchy that incorporates the WordNet semantic net and extracts answers after performing unifications on the semantic forms of the question and its candidate answers. To rule out erroneous answers, it provides justification option, implemented as an abductive proof. In TREC-9, FALCON generated a score of 58% for short answers and 76% for long answers.
- Resource Discovery Using Z39.50: Promise and Reality
- This paper discusses the Z39.50 protocol. The ANSI/NISO Z39.50 protocol for information retrieval addresses the complex challenges of intersystem communication. Original uses envisioned for the protocol look very little like current implementations and uses. In the 1980s, users on one library catalog system would search and retrieve bibliographic records on a remote system. By the late 1990s, there was a need for discovering networked resources and integrating access to them. Yet, the Z39.50 protocol has addressed both these scenarios. This paper provides a portrayal of Z39.50 that explains its flexibility in response to a variety of information retrieval requirements in the networked environment.