keymanticES: Semantic Keyword Entity Search Mechanism in Dataspaces
Dan Yang, Derong Shen, Tiezheng Nie, Yu Ge, Yue Kou
Abstract
Dan Yang, Derong Shen, Tiezheng Nie, Yu Ge, Yue Kou
Abstract
Due to specific features of dataspaces Key word search in dataspaces is different from those in web and in relational databases.Some existed keyword search techniques can not be applied or satisfy completely in datasapces environment.The ambiguous semantic caused by simple and unstructured features of keyword search is hard to understand user′s query intent and satisfy user′s information requirement.This paper proposes a novel semantic keyword entity search mechanism: keymanticES in dataspaces,and focuses on query intent disambiguates of keyword search which effectively resolves the semantic ambiguous problem and improves the precision of keyword search.Experiments results show the effectiveness and correctness of the proposed approach.
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Due to specific features of dataspaces Key word search in dataspaces is different from those in web and in relational databases.Some existed keyword search techniques can not be applied or satisfy completely in datasapces environment.The ambiguous semantic caused by simple and unstructured features of keyword search is hard to understand user′s query intent and satisfy user′s information requirement.This paper proposes a novel semantic keyword entity search mechanism: keymanticES in dataspaces,and focuses on query intent disambiguates of keyword search which effectively resolves the semantic ambiguous problem and improves the precision of keyword search.Experiments results show the effectiveness and correctness of the proposed approach.
Key concepts: Computer science, Semantic search, Information retrieval, Keyword search, Web search query, Keyword density, Search engine, Search-oriented architecture