An empirical study of vocabulary relatedness and its application to recommender systems
G. Cheng, S. Gong, and Y. Qu. Proceedings of the 10th international conference on The semantic web - Volume Part I, page 98--113. Berlin, Heidelberg, Springer-Verlag, (2011)
Abstract
When thousands of vocabularies having been published on the SemanticWeb by various authorities, a question arises as to how they are related to each other. Existing work has mainly analyzed their similarity. In this paper, we inspect the more general notion of relatedness, and characterize it from four angles: well-defined semantic relatedness, lexical similarity in contents, closeness in expressivity and distributional relatedness. We present an empirical study of these measures on a large, real data set containing 2,996 vocabularies, and 15 million RDF documents that use them. Then, we propose to apply vocabulary relatedness to the problem of post-selection vocabulary recommendation. We implement such a recommender service as part of a vocabulary search engine, and test its effectiveness against a handcrafted gold standard.
Description
An empirical study of vocabulary relatedness and its application to recommender systems
%0 Conference Paper
%1 cheng2011empirical
%A Cheng, Gong
%A Gong, Saisai
%A Qu, Yuzhong
%B Proceedings of the 10th international conference on The semantic web - Volume Part I
%C Berlin, Heidelberg
%D 2011
%I Springer-Verlag
%K relatedness vocabulary
%P 98--113
%T An empirical study of vocabulary relatedness and its application to recommender systems
%U http://dl.acm.org/citation.cfm?id=2063016.2063024
%X When thousands of vocabularies having been published on the SemanticWeb by various authorities, a question arises as to how they are related to each other. Existing work has mainly analyzed their similarity. In this paper, we inspect the more general notion of relatedness, and characterize it from four angles: well-defined semantic relatedness, lexical similarity in contents, closeness in expressivity and distributional relatedness. We present an empirical study of these measures on a large, real data set containing 2,996 vocabularies, and 15 million RDF documents that use them. Then, we propose to apply vocabulary relatedness to the problem of post-selection vocabulary recommendation. We implement such a recommender service as part of a vocabulary search engine, and test its effectiveness against a handcrafted gold standard.
%@ 978-3-642-25072-9
@inproceedings{cheng2011empirical,
abstract = {When thousands of vocabularies having been published on the SemanticWeb by various authorities, a question arises as to how they are related to each other. Existing work has mainly analyzed their similarity. In this paper, we inspect the more general notion of relatedness, and characterize it from four angles: well-defined semantic relatedness, lexical similarity in contents, closeness in expressivity and distributional relatedness. We present an empirical study of these measures on a large, real data set containing 2,996 vocabularies, and 15 million RDF documents that use them. Then, we propose to apply vocabulary relatedness to the problem of post-selection vocabulary recommendation. We implement such a recommender service as part of a vocabulary search engine, and test its effectiveness against a handcrafted gold standard.},
acmid = {2063024},
added-at = {2012-09-03T15:48:46.000+0200},
address = {Berlin, Heidelberg},
author = {Cheng, Gong and Gong, Saisai and Qu, Yuzhong},
biburl = {https://www.bibsonomy.org/bibtex/28acdd53fce58fe02092333a4e89e9caa/dbenz},
booktitle = {Proceedings of the 10th international conference on The semantic web - Volume Part I},
description = {An empirical study of vocabulary relatedness and its application to recommender systems},
interhash = {3c539da36cb3fd5c6d5a2e0684f3b854},
intrahash = {8acdd53fce58fe02092333a4e89e9caa},
isbn = {978-3-642-25072-9},
keywords = {relatedness vocabulary},
location = {Bonn, Germany},
numpages = {16},
pages = {98--113},
publisher = {Springer-Verlag},
series = {ISWC'11},
timestamp = {2013-07-31T15:39:42.000+0200},
title = {An empirical study of vocabulary relatedness and its application to recommender systems},
url = {http://dl.acm.org/citation.cfm?id=2063016.2063024},
year = 2011
}