FAQ answering on WWW using shallow language understanding
While advertising some product, service or activity, information providers often put forward so called frequently asked questions (FAQ). The answers to these questions help people to understand details of the information. The research presented in this paper will help to improve users’ interaction with information supplied through an FAQ collection on the World Wide Web. Problems with existing FAQ lists are observed and solutions to these problems proposed.
In this paper, the development of an automated Web-based FAQ answering system, which provides pre-stored answers to users’ questions asked in natural English, is discussed. The natural language interface makes users’ interaction with the system more enjoyable, as well as lets the FAQ authors find out what questions the users actually have. The system maintains its own question-and-answer base. The structure of the database, which is implemented as a relational database, as well as the searching algorithms, are discussed. The system uses shallow language understanding to process questions. Within the scope of this research, the Prioritized Keyword Matching algorithm, which is based on distinguishing primary and secondary keywords, has been developed. It is used to match the user’s question against separate entries in a narrow subset of the question-and-answer base.
KeywordsFAQ frequently asked questions FAQ answering question answering WWW shallow language understanding keyword matching
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