Semantic search for matching user requests with profiled enterprises


获取原文并翻译 | 示例


Semantic search is an important approach that promises significant improvements for customers to identify products of their interest. To perform semantic search, enterprises need to publish semantically enriched descriptions of their offered goods and services; then a customer expresses his/her request, in an easy Google like fashion, by providing a list of desired features. If enterprise offerings and customer requests are based on the same vocabulary (i.e., ontology), they can be semantically matched by using advanced semantic methods. In this paper, we propose an ontology-based method aimed at finding the best matches between a user request and the services offered by different enterprises. We assume that in a given business ecosystem (in the paper, as an example, the tourism sector) a group of SMEs agree on the adoption of a reference ontology, used to build the company profiles on the basis of the offered services. Accordingly, a user request, represented by a set of desired features, is expressed in terms of the reference ontology terminology (i.e., concepts). In this paper, we illustrate SemSim, a method used to collectively search the SME profiles to identify the services that match at best the user request. SemSim is based on the well-known information content approach used to evaluate the semantic similarity between concepts. The experimental results show that our proposal performs better than some of the most representative similarity search methods proposed in the literature.
机译:语义搜索是一种重要的方法,有望为客户识别自己感兴趣的产品带来重大改进。为了进行语义搜索,企业需要发布对其提供的商品和服务的语义丰富的描述;然后客户通过提供所需功能的列表,以类似于Google的简单方式表达其要求。如果企业产品和客户请求基于相同的词汇表(即本体),则可以使用高级语义方法在语义上进行匹配。在本文中,我们提出了一种基于本体的方法,旨在找到用户请求和不同企业提供的服务之间的最佳匹配。我们假设在给定的业务生态系统中(例如,本文以旅游业为例),一组中小型企业同意采用参考本体,该本体用于在提供的服务的基础上建立公司简介。因此,以参考本体术语(即,概念)表达由一组期望特征表示的用户请求。在本文中,我们说明了SemSim,这是一种用于集体搜索SME配置文件以识别最能满足用户要求的服务的方法。 SemSim基于众所​​周知的信息内容方法,用于评估概念之间的语义相似性。实验结果表明,我们的建议比文献中提出的一些最具代表性的相似性搜索方法表现更好。



  • 外文文献
  • 中文文献
  • 专利
  • 写作辅导
  • 期刊发表


京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号