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Algorithms for recollection of search terms based on the Wikipedia category structure

机译:基于Wikipedia类别结构重新收集搜索项的算法

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摘要

The common user interface for a search engine consists of a text field where the user can enter queries consisting of one or more keywords. Keyword query based search engines work well when the users have a clear vision what they are looking for and are capable of articulating their query using the same terms as indexed. For our multimedia database containing 202,868 items with text descriptions, we supplement such a search engine with a category-based interface whose category structure is tailored to the content of the database. This facilitates browsing and offers the users the possibility to look for named entities, even if they forgot their names. We demonstrate that this approach allows users who fail to recollect the name of named entities to retrieve data with little effort. In all our experiments, it takes 1 query on a category and on average 2.49 clicks, compared to 5.68 queries on the database's traditional text search engine for a 68.3% success probability or 6.01 queries when the user also turns to Google, for a 97.1% success probability.
机译:搜索引擎的通用用户界面由一个文本字段组成,用户可以在其中输入由一个或多个关键字组成的查询。当用户对所要查找的内容有清晰的了解并且能够使用与索引相同的术语来表达其查询时,基于关键字查询的搜索引擎会很好地工作。对于包含202868个带有文本描述的项目的多媒体数据库,我们使用基于类别的界面来补充这种搜索引擎,该界面的类别结构适合于数据库的内容。这有助于浏览,即使用户忘记了名称,用户也可以查找命名实体。我们证明了这种方法可以使无法重新收集命名实体名称的用户轻松获取数据。在我们所有的实验中,一个类别平均需要进行1次查询,平均点击次数为2.49次,相比之下,数据库传统文本搜索引擎上的查询为5.68次,则成功概率为68.3%,而用户也转向Google时为6.01次查询,则为97.1%成功概率。

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