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Chemical-Text HybrDE Search Engines

机译:化学测试混合搜索引擎

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摘要

As the amount of chemical literature increases, it is critical that researchers be enabled to accurately locate documents related to a particular aspect of a given compound. Existing solutions, based on text and chemical search engines alone, suffer from the inclusion of "false negative" and "false positive" results, and cannot accommodate diverse repertoire of formats Currently available for chemical documents. To address these concerns, we developed an approach called Entity-Canonical Keyword Indexing (ECKI), which converts a chemical entity embedded in a data source into its canonical keyword representation prior to being indexed by text search engines. We implemented ECKI using Microsoft, Office SharePoint Server Search, and the resultant hybrDE search engine not only supported complex mixed chemical and keyword queries but also was applied to both intranet and Internet environments. We envision that the adoption of ECKI will empower researchers to pose more complex search questions that were not readily attainable previously and to obtain answers at much improved speed and accuracy.
机译:随着化学文献数量的增加,使研究人员能够准确定位与给定化合物特定方面有关的文档至关重要。仅基于文本和化学搜索引擎的现有解决方案会遭受包括“假阴性”和“假阳性”结果的问题,并且不能适应当前可用于化学文档的各种格式。为了解决这些问题,我们开发了一种称为实体标准关键字索引(ECKI)的方法,该方法将嵌入数据源中的化学实体转换为标准关键字表示形式,然后再由文本搜索引擎建立索引。我们使用Microsoft,Office SharePoint Server Search和Office SharePoint Server Search实施了ECKI,由此产生的hybrDE搜索引擎不仅支持复杂的化学和关键字混合查询,而且还应用于Intranet和Internet环境。我们设想,采用ECKI将使研究人员能够提出以前无法轻易解决的更复杂的搜索问题,并以大大提高的速度和准确性获得答案。

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