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BOSS: context-enhanced search for biomedical objects

机译：BOSS：对生物医学对象的上下文增强搜索

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BackgroundThere exist many academic search solutions and most of them can be put on either ends of spectrum: general-purpose search and domain-specific "deep" search systems. The general-purpose search systems, such as PubMed, offer flexible query interface, but churn out a list of matching documents that users have to go through the results in order to find the answers to their queries. On the other hand, the "deep" search systems, such as PPI Finder and iHOP, return the precompiled results in a structured way. Their results, however, are often found only within some predefined contexts. In order to alleviate these problems, we introduce a new search engine, BOSS, Biomedical Object Search System.MethodsUnlike the conventional search systems, BOSS indexes segments, rather than documents. A segment refers to a Maximal Coherent Semantic Unit (MCSU) such as phrase, clause or sentence that is semantically coherent in the given context (e.g., biomedical objects or their relations). For a user query, BOSS finds all matching segments, identifies the objects appearing in those segments, and aggregates the segments for each object. Finally, it returns the ranked list of the objects along with their matching segments.ResultsThe working prototype of BOSS is available at http://boss.korea.ac.kr. The current version of BOSS has indexed abstracts of more than 20 million articles published during last 16 years from 1996 to 2011 across all science disciplines.ConclusionBOSS fills the gap between either ends of the spectrum by allowing users to pose context-free queries and by returning a structured set of results. Furthermore, BOSS exhibits the characteristic of good scalability, just as with conventional document search engines, because it is designed to use a standard document-indexing model with minimal modifications. Considering the features, BOSS notches up the technological level of traditional solutions for search on biomedical information.
机译：背景技术存在许多学术搜索解决方案，其中大多数可以放在频谱的两端：通用搜索和特定领域的“深度”搜索系统。通用搜索系统（例如PubMed）提供了灵活的查询界面，但会列出用户必须仔细阅读结果才能找到其查询答案的匹配文档列表。另一方面，“深度”搜索系统（例如PPI Finder和iHOP）以结构化的方式返回预编译的结果。但是，通常只能在某些预定义的上下文中找到它们的结果。为了减轻这些问题，我们引入了一个新的搜索引擎BOSS生物医学对象搜索系统。方法与常规搜索系统不同，BOSS索引段而不是文档。段是指在给定上下文中（例如生物医学对象或其关系）在语义上连贯的最大连贯语义单元（MCSU），例如短语，从句或句子。对于用户查询，BOSS会找到所有匹配的段，识别出现在这些段中的对象，然后汇总每个对象的段。最后，它返回对象的排序列表及其匹配的段。结果BOSS的工作原型可从http://boss.korea.ac.kr获得。当前版本的BOSS已索引1996年至2011年过去16年间所有科学学科中超过2000万篇文章的摘要。结论BOSS通过允许用户提出上下文无关的查询并返回来填补了两端之间的空白。结构化的结果集。此外，与传统的文档搜索引擎一样，BOSS表现出良好的可伸缩性的特性，因为它被设计为使用标准的文档索引模型并进行了最小的修改。考虑到这些功能，BOSS提升了传统解决方案在生物医学信息搜索方面的技术水平。

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