Fine-grained Full-text Search

Most conventional text retrieval methods are designed to search for documents. However, users often do not require documents themselves, but are searching for specific 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. 1998-12 (Partially updated on 2009-7)