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Extending Term Suggestion with Author Names

机译:与作者名称扩展的术语建议

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摘要

Term suggestion or recommendation modules can help users to formulate their queries by mapping their personal vocabularies onto the specialized vocabulary of a digital library. While we examined actual user queries of the social sciences digital library Sowiport we could see that nearly one third of the users were explicitly looking for author names rather than terms. Common term recommenders neglect this fact. By picking up the idea of polyrepresentation we could show that in a standardized IR evaluation setting we can significantly increase the retrieval performances by adding topical-related author names to the query. This positive effect only appears when the query is additionally expanded with thesaurus terms. By just adding the author names to a query we often observe a query drift which results in worse results.
机译:术语建议或建议模块可以帮助用户通过将其个人词汇表映射到数字图书馆的专业词汇来帮助用户询问他们的查询。虽然我们审查了社会科学的实际用户查询,数字图书馆索维片我们可以看到,近三分之一的用户明确寻找作者名称而不是条款。共同的术语推荐者忽视了这一事实。通过拾取多项资格的想法,我们可以表明,在标准化的IR评估设置中,我们可以通过将与题称相关的作者名称添加到查询来显着提高检索性能。当查询另外扩展时,才会出现这种积极效果。只需将作者姓名添加到查询,我们经常观察一个导致更糟糕的结果的查询漂移。

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