926,348 research outputs found

    Automatically attaching web pages to an ontology

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    This paper describes a proposed system for automatically attaching material from the world wide web to concepts in an ontology. The motivation for this research stems from the Diogene project, which requires the project's own databases of learning objects to be augmented with additional resources from the web. Two main approaches to this problem are being taken: one using ontology mapping, and another based on the conventional text search facilities of the web, covered in this paper. By generating queries based on the concepts in the ontology, the aim is to retrieve material from the web, and then filter it to ensure its proper correspondence with a concept. The Diogene system will be briefly outlined, before the query-generation system is described. A small pilot experiment, designed to provide some initial results and insight into the problem, is then presented

    A User-Centered Concept Mining System for Query and Document Understanding at Tencent

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    Concepts embody the knowledge of the world and facilitate the cognitive processes of human beings. Mining concepts from web documents and constructing the corresponding taxonomy are core research problems in text understanding and support many downstream tasks such as query analysis, knowledge base construction, recommendation, and search. However, we argue that most prior studies extract formal and overly general concepts from Wikipedia or static web pages, which are not representing the user perspective. In this paper, we describe our experience of implementing and deploying ConcepT in Tencent QQ Browser. It discovers user-centered concepts at the right granularity conforming to user interests, by mining a large amount of user queries and interactive search click logs. The extracted concepts have the proper granularity, are consistent with user language styles and are dynamically updated. We further present our techniques to tag documents with user-centered concepts and to construct a topic-concept-instance taxonomy, which has helped to improve search as well as news feeds recommendation in Tencent QQ Browser. We performed extensive offline evaluation to demonstrate that our approach could extract concepts of higher quality compared to several other existing methods. Our system has been deployed in Tencent QQ Browser. Results from online A/B testing involving a large number of real users suggest that the Impression Efficiency of feeds users increased by 6.01% after incorporating the user-centered concepts into the recommendation framework of Tencent QQ Browser.Comment: Accepted by KDD 201

    Semantic Transformation of Web Services

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    Web services have become the predominant paradigm for the development of distributed software systems. Web services provide the means to modularize software in a way that functionality can be described, discovered and deployed in a platform independent manner over a network (e.g., intranets, extranets and the Internet). The representation of web services by current industrial practice is predominantly syntactic in nature lacking the fundamental semantic underpinnings required to fulfill the goals of the emerging Semantic Web. This paper proposes a framework aimed at (1) modeling the semantics of syntactically defined web services through a process of interpretation, (2) scop-ing the derived concepts within domain ontologies, and (3) harmonizing the semantic web services with the domain ontologies. The framework was vali-dated through its application to web services developed for a large financial system. The worked example presented in this paper is extracted from the se-mantic modeling of these financial web services
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