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Information Systems Frontiers
Erschienen in: Information Systems Frontiers 5/2017

13.07.2016

Building spatial temporal relation graph of concepts pair using web repository

verfasst von: Zheng Xu, Junyu Xuan, Yunhuai Liu, Kim-Kwang Raymond Choo, Lin Mei, Chuanping Hu

Erschienen in: Information Systems Frontiers | Ausgabe 5/2017

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Abstract

Mining semantic relations between concepts underlies many fundamental tasks including natural language processing, web mining, information retrieval, and web search. In order to describe the semantic relation between concepts, in this paper, the problem of automatically generating spatial temporal relation graph (STRG) of semantic relation between concepts is studied. The spatial temporal relation graph of semantic relation between concepts includes relation words, relation sentences, relation factor, relation graph, faceted feature, temporal feature, and spatial feature. The proposed method can automatically generate the spatial temporal relation graph (STRG) of semantic relation between concepts, which is different from the manually generated annotation repository such as WordNet and Wikipedia. Moreover, the proposed method does not need any prior knowledge such as ontology or the hierarchical knowledge base such as WordNet. Empirical experiments on real dataset show that the proposed algorithm is effective and accurate.
Vorheriger Artikel Improving the freshness of the search engines by a probabilistic approach based incremental crawler
Nächster Artikel An enhanced text detection technique for the visually impaired to read text

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Fußnoten
1
Wordnet.princeton.edu
 
11
The searching date is 2015–08-12.
 
12
The data was get in the data 1/14/2012
 
13
The time interval of them are 8/16/2015–8/22/2015 and the location is US
 
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Metadaten
Titel
Building spatial temporal relation graph of concepts pair using web repository
verfasst von
Zheng Xu
Junyu Xuan
Yunhuai Liu
Kim-Kwang Raymond Choo
Lin Mei
Chuanping Hu
Publikationsdatum
13.07.2016
Verlag
Springer US
Erschienen in
Information Systems Frontiers / Ausgabe 5/2017
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI
https://doi.org/10.1007/s10796-016-9676-4

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