| Autor: | Gary Thomas, Xien Fan, Peter A. Ng, Fang Sheng |
|---|---|
| Rok vydání: | 2001 |
| Předmět: |
Web search query
business.industry Computer science Document management system Document clustering computer.software_genre Query language Query expansion Web query classification General Earth and Planetary Sciences Artificial intelligence Inference engine Document retrieval business computer Natural language processing |
| Zdroj: | Journal of Systems Integration. 10:411-436 |
| ISSN: | 0925-4676 |
| DOI: | 10.1023/a:1011262119636 |
| Popis: | This paper presents a knowledge-based approach to effective document retrieval. This approach is based on a dual document model that consists of a document type hierarchy and a folder organization. A predicate-based document query language is proposed to enable users to precisely and accurately specify the search criteria and their knowledge about the documents to be retrieved. A guided search tool is developed as an intelligent natural language oriented user interface to assist users formulating queries. Supported by an intelligent question generator, an inference engine, a question base, and a predicate-based query composer, the guided search collects the most important information known to the user to retrieve the documents that satisfy users' particular interests. A knowledge-based query processing and search engine is devised as the core component in this approach. Algorithms are developed for the search engine to effectively and efficiently retrieve the documents that match the query. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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