Ontology-driven query expansion and search results organization

搜索是许多以信息为中心的活动的重要组成部分。支持搜索任务的传统方法集中在基于关键字的匹配和排名的列表表示。当用户能够准确地描述他们所寻求的是什么，并且当文档中使用的术语与用户所使用的术语相同时，这种方法很有效。然而，当搜索者的查询、正在搜索的集合或两者中存在很大程度的模糊性时，这种基于关键字的方法变得不那么有效。例如，如果招聘人员和申请人都使用相同的术语来描述特定技能，则在工作申请集合中搜索该技能将成功，如果术语不匹配，则将失败。因此，搜索者有必要根据他们对该领域的知识执行一系列搜索任务，并花费大量精力来合成搜索结果的排名列表。

Search is a vital part of many information-centric activities. Traditional approaches for supporting search tasks focus on keyword-based matching and ranked listed representations. This works well when the searcher can accurately describe what it is that they are seeking, and when the terminology used in the documents is the same as that used by the searcher. However, such keyword-based approaches become less effective when there is a large degree of ambiguity within the searcher's query, the collection being searched, or both. For example, searching within a collection of job applications for a particular skill will be successful if both the recruiter and applicant use the same terms to describe this skill, and will fail if there is a mismatch in their terminology. As a result, it is necessary for searchers to perform a series of search tasks based on their knowledge of the domain, and expend significant effort in synthesizing the ranked lists of search results.