Abstract With the emergence of Web 2.0, the amount of user-generated web data has sharply increased. Thus, many studies have proposed techniques to extract wisdom from these user-generated datasets. Some of these works have focused on extracting semantic relationships through the use of search logs or social annotations, but only hierarchical relationships have been considered. The goal of this paper is to detect various semantic relationships (hierarchical and non-hierarchical) between concepts using search logs and social annotations. The experimental results demonstrate that our proposed approach constructs adequate relationships.
%0 Journal Article
%1 Hsu201527
%A Hsu, Pei-Ling
%A Hsieh, Hsiao-Shan
%A Liang, Jheng-He
%A Chen, Yi-Shin
%D 2015
%J Web Semantics: Science, Services and Agents on the World Wide Web
%K 2015 ontological_relationships ontology_learning semantics user-generated_data
%P 27 - 38
%R http://dx.doi.org/10.1016/j.websem.2014.11.004
%T Mining various semantic relationships from unstructured user-generated web data
%U http://www.sciencedirect.com/science/article/pii/S1570826814001073
%V 31
%X Abstract With the emergence of Web 2.0, the amount of user-generated web data has sharply increased. Thus, many studies have proposed techniques to extract wisdom from these user-generated datasets. Some of these works have focused on extracting semantic relationships through the use of search logs or social annotations, but only hierarchical relationships have been considered. The goal of this paper is to detect various semantic relationships (hierarchical and non-hierarchical) between concepts using search logs and social annotations. The experimental results demonstrate that our proposed approach constructs adequate relationships.
@article{Hsu201527,
abstract = {Abstract With the emergence of Web 2.0, the amount of user-generated web data has sharply increased. Thus, many studies have proposed techniques to extract wisdom from these user-generated datasets. Some of these works have focused on extracting semantic relationships through the use of search logs or social annotations, but only hierarchical relationships have been considered. The goal of this paper is to detect various semantic relationships (hierarchical and non-hierarchical) between concepts using search logs and social annotations. The experimental results demonstrate that our proposed approach constructs adequate relationships. },
added-at = {2016-01-02T03:39:16.000+0100},
author = {Hsu, Pei-Ling and Hsieh, Hsiao-Shan and Liang, Jheng-He and Chen, Yi-Shin},
biburl = {https://www.bibsonomy.org/bibtex/2479ec50752c916a777455310703fac46/hangdong},
doi = {http://dx.doi.org/10.1016/j.websem.2014.11.004},
interhash = {37db8dd4c34e8d754926878d72ac17c9},
intrahash = {479ec50752c916a777455310703fac46},
issn = {1570-8268},
journal = {Web Semantics: Science, Services and Agents on the World Wide Web },
keywords = {2015 ontological_relationships ontology_learning semantics user-generated_data},
pages = {27 - 38},
timestamp = {2016-09-21T10:37:41.000+0200},
title = {Mining various semantic relationships from unstructured user-generated web data },
url = {http://www.sciencedirect.com/science/article/pii/S1570826814001073},
volume = 31,
year = 2015
}