NDLI: Entity Resolution Approach of Data Stream Management Systems

Content Provider	Springer Nature Link
Author	Kim, Taehong Hwang, Mi Nyeong Kim, Young Min Jeong, Do Heon
Copyright Year	2016
Abstract	Owing to the technological advancements in Semantic Web and sensor networks, a large amount of data has been produced in association with the open data policy. However, data stream management systems that process stream data have focused on the processing of a large amount of data with little priority on data identification, integration, and external linkage. Furthermore, entity resolution is focused mainly on static database-based technologies. In this study, a real-time stream data processing architecture that can perform the integration and entity resolution of streaming-type heterogeneous input data and interlink with external data is designed. To achieve this goal, a light adapter to integrate heterogeneous data into standard scheme and blocking technique to reduce comparison candidates are applied. The implemented data adapters shows 4 times higher throughput than open source data parsers and the entity resolution results with streaming data shows similar performance with the static data sets. The proposed streaming data entity resolution architecture is expected to form the basis of data integration research that can integrate various information sources of data efficiently, enrich internal data.
Starting Page	1621
Ending Page	1634
Page Count	14
File Format	PDF
ISSN	09296212
Journal	Wireless Personal Communications
Volume Number	91
Issue Number	4
e-ISSN	1572834X
Language	English
Publisher	Springer US
Publisher Date	2016-04-11
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	IoT Streaming data processing Dynamic entity resolution Streaming linked data Entity resolution Blocking entity Data stream management system Communications Engineering, Networks Signal,Image and Speech Processing Computer Communication Networks
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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