标题:Associated Index for Big Structured and Unstructured Data
作者:Zhu, Chunying; Li, Qingzhong; Kong, Lanju; Wang, Xiangwei; Hong, Xiaoguang
通讯作者:Li, Qingzhong
作者机构:[Zhu, Chunying; Li, Qingzhong; Kong, Lanju; Hong, Xiaoguang] Shandong Univ, Sch Comp Sci & Technol, Jinan 250100, Peoples R China.; [Wang, Xiangwei] 更多
会议名称:16th International Conference on Web-Age Information Management (WAIM)
会议日期:JUN 08-10, 2015
来源:WEB-AGE INFORMATION MANAGEMENT (WAIM 2015)
出版年:2015
卷:9098
页码:567-570
DOI:10.1007/978-3-319-21042-1_64
摘要:In big data epoch, one of the major challenges is the large volume of mixed structured and unstructured data. Because of different form, structured and unstructured data are often considered apart from each other. However, they may speak about the same entities of the world. If a query involves both structured data and its unstructured counterpart, it is inefficient to execute it separately. The paper presents a novel index structure tailored towards associations between structured and unstructured data, based on entity co-occurrences. It is also a semantic index represented as RDF graphs which describes the semantic relationships among entities. Experiments show that the associated index can not only provide apposite information but also execute queries efficiently.
收录类别:CPCI-S;EI;SCOPUS
Scopus被引频次:1
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937440059&doi=10.1007%2f978-3-319-21042-1_64&partnerID=40&md5=24af00330812466c6d5a8edfe02dbf3f
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