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Translating dialects in search: Mapping between specialized languages of discourse and documentary languages.

机译:在搜索中翻译方言:话语专业语言和文献语言之间的映射。

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摘要

The biggest problem in searching an information system is to find the appropriate search terms that not only represent the searcher's information need but also match the language used in the information system. This is a translation problem between a specialized dialect of discourse and the documentary language of the information system.; Discourse dialects evolve within specialized communities. They differ from general language and other communities' dialects in terminology (e.g. terms of art, jargon) and grammar patterns. A documentary language is the language used for document representation in an information system. A bibliographic database and its documentary language usually cover more than one domain of discourse.; This dissertation describes a mechanism that will provide a translation aid between specialized languages and the documentary language by suggesting appropriate search terms for a searcher's query in relation to the searcher's domain of discourse. With this kind of vocabulary support in the search process, the different specialized vocabularies can be disambiguated within the information system. Different perspectives on a topic can be represented to the searcher (based on the different discourses of the topic in the collection), which will help in navigating and exploring this information space more effectively.; The search term recommender system, based on statistical associations between specialized language terms and controlled vocabulary terms, is introduced and its applications for automatic text categorization, query expansion and reformulation, and terminology mapping are described. The search term recommender methodology is tested on three specialties in the Inspec bibliographical database and 33 specialties in the Ohsumed database in a text classification application. It is demonstrated that search term recommender systems are more effective when specialty-based.
机译:搜索信息系统中最大的问题是找到合适的搜索词,这些词不仅代表搜索者的信息需求,而且与信息系统中使用的语言相匹配。这是一个专门的话语方言和信息系统的文献语言之间的翻译问题。话语方言在专门社区内发展。它们在术语(例如艺术术语,专业术语)和语法模式方面不同于一般语言和其他社区的方言。文献语言是信息系统中用于文献表示的语言。书目数据库及其文献语言通常涵盖多个领域。本文描述了一种机制,该机制将通过针对搜索者的查询领域相对于搜索者的话语领域提出合适的搜索词来为专业语言和文献语言之间提供翻译帮助。借助搜索过程中的这种词汇支持,可以在信息系统中消除不同专业词汇的歧义。可以向搜索者表示某个主题的不同观点(基于集合中该主题的不同论述),这将有助于更有效地导航和探索此信息空间。介绍了基于专业语言术语和受控词汇术语之间的统计关联的搜索词推荐系统,并描述了其在自动文本分类,查询扩展和重构以及术语映射中的应用。在文本分类应用程序中,对Inspec书目数据库中的三个专业和Ohsumed数据库中的33个专业测试了搜索词推荐程序方法。结果表明,基于专业的搜索词推荐系统更为有效。

著录项

  • 作者

    Petras, Vivien.;

  • 作者单位

    University of California, Berkeley.;

  • 授予单位 University of California, Berkeley.;
  • 学科 Language Linguistics.; Information Science.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 257 p.
  • 总页数 257
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 语言学;信息与知识传播;
  • 关键词

  • 入库时间 2022-08-17 11:41:00

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