Leydesdorff, L. & Welbers, K.: The semantic mapping of words and co-words in contexts. , 2010
[Volltext]
Meaning can be generated when information is related at a systemic level.Such a system can be an observer, but also a discourse, for example,operationalized as a set of documents. The measurement of semantics assimilarity in patterns (correlations) and latent variables (factor analysis)has been enhanced by computer techniques and the use of statistics; forexample, in "Latent Semantic Analysis". This communication provides anintroduction, an example, pointers to relevant software, and summarizes thechoices that can be made by the analyst. Visualization ("semantic mapping") isthus made more accessible.
@misc{leydesdorff2010semantic,
author = {Leydesdorff, Loet and Welbers, Kasper},
title = {The semantic mapping of words and co-words in contexts},
year = {2010},
note = {cite arxiv:1011.5209},
url = {http://arxiv.org/abs/1011.5209},
keywords = {context, semantics, words, ol_web2.0, widely_related},
abstract = { Meaning can be generated when information is related at a systemic level.Such a system can be an observer, but also a discourse, for example,operationalized as a set of documents. The measurement of semantics assimilarity in patterns (correlations) and latent variables (factor analysis)has been enhanced by computer techniques and the use of statistics; forexample, in "Latent Semantic Analysis". This communication provides anintroduction, an example, pointers to relevant software, and summarizes thechoices that can be made by the analyst. Visualization ("semantic mapping") isthus made more accessible.}
}
man Yeung, C.; Gibbins, N. & Shadbolt, N.: Mutual Contextualization in Tripartite Graphs of Folksonomies. In: Aberer, K.; Choi, K.-S.; Noy, N.; Allemang, D.; Lee, K.-I.; Nixon, L.; Golbeck, J.; Mika, P.; Maynard, D.; Mizoguchi, R.; Schreiber, G. & Cudré-Mauroux, P. (Hrsg.): The Semantic Web. Berlin / Heidelberg: Springer, 2007 (Lecture Notes in Computer Science 4825), S. 966-970
[Volltext]
The use of tags to describe Web resources in a collaborative manner has experienced rising popularity among Web users in recent years. The product of such activity is given the name folksonomy, which can be considered as a scheme of organizing information in the users’ own way. This research work attempts to analyze tripartite graphs – graphs involving users, tags and resources – of folksonomies and discuss how these elements acquire their semantics through their associations with other elements, a process we call mutual contextualization. By studying such process, we try to identify solutions to problems such as tag disambiguation, retrieving documents of similar topics and discovering communities of users. This paper describes the basis of the research work, mentions work done so far and outlines future plans.
@incollection{springerlink:10.1007/978-3-540-76298-0_79,
author = {man Yeung, Ching and Gibbins, Nicholas and Shadbolt, Nigel},
title = {Mutual Contextualization in Tripartite Graphs of Folksonomies},
editor = {Aberer, Karl and Choi, Key-Sun and Noy, Natasha and Allemang, Dean and Lee, Kyung-Il and Nixon, Lyndon and Golbeck, Jennifer and Mika, Peter and Maynard, Diana and Mizoguchi, Riichiro and Schreiber, Guus and Cudré-Mauroux, Philippe},
booktitle = {The Semantic Web},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
address = {Berlin / Heidelberg},
year = {2007},
volume = {4825},
pages = {966-970},
url = {http://dx.doi.org/10.1007/978-3-540-76298-0_79},
doi = {10.1007/978-3-540-76298-0_79},
keywords = {context, folksonomies, ol_web2.0, tagging},
abstract = {The use of tags to describe Web resources in a collaborative manner has experienced rising popularity among Web users in recent years. The product of such activity is given the name folksonomy, which can be considered as a scheme of organizing information in the users’ own way. This research work attempts to analyze tripartite graphs – graphs involving users, tags and resources – of folksonomies and discuss how these elements acquire their semantics through their associations with other elements, a process we call mutual contextualization. By studying such process, we try to identify solutions to problems such as tag disambiguation, retrieving documents of similar topics and discovering communities of users. This paper describes the basis of the research work, mentions work done so far and outlines future plans.}
}