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Fine-grained Full-text Search

Yasusi Kanada, Not yet published, 1998.

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Abstract: Most conventional text retrieval methods are designed to search for documents. However, users often do not require documents themselves, but are searching for spe-cific information that may come from a large collection of texts quickly. To satisfy this need, we have developed a model and two methods for fine-grained searching. The unit of search in this model is called an atom, and it can be a sentence or smaller syntactic unit. A score, i.e., a relevance value, is defined for each atom and for each query, and the score is propagated between atoms. By using the two methods, excerpts from texts surrounding the search-result items and/or hyperlinks to the document parts that include the items are displayed. Multiple topics in a document can be separately listed in a search result. Evaluation of two prototypes, using a conventional full-text search engine as is or with only a small modification, has demonstrated that these methods are feasible and can decrease the search cost in terms of time and effort for users.

Introduction to the research theme: Axis-Specified Search (Thematic Search)

Keywords: Text search, Fine-grained search, Passage retrieval

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