Probabilistic latent semantic analyses (plsa) in bibliometric analysis for technology forecasting

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Bibliographic Details
Main Author: Zan Wang
Format: Artículo científico
Language:en
Published: Universidad Alberto Hurtado 2007
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author Zan Wang
author_facet Zan Wang
contents Probabilistic latent semantic analyses (plsa) in bibliometric analysis for technology forecasting Zan Wang Y.C. Tsim W.S. Yeung K.C. Chan Jinlan Liu Ingeniería Bibliometric analysis technology forecasting latent semantic analysis probabilistic latent semantic analysis Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA) has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA) which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency. Probabilistic Latent Semantic Analyses (PLSA) in Bibliometric Analysis for Technology Forecasting 2007 artículo científico 0718-2724 https://www.redalyc.org/articulo.oa?id=84720103 en http://www.redalyc.org/revista.oa?id=847 Journal of Technology Management & Innovation application/pdf Universidad Alberto Hurtado Journal of Technology Management & Innovation (Chile) Num.1 Vol.2
format Artículo científico
id redalyc_84720103
institution Redalyc
language en
publishDate 2007
publisher Universidad Alberto Hurtado
spellingShingle Probabilistic latent semantic analyses (plsa) in bibliometric analysis for technology forecasting
Zan Wang
Ingeniería
Bibliometric analysis
technology forecasting
latent semantic analysis
probabilistic latent semantic analysis
Probabilistic latent semantic analyses (plsa) in bibliometric analysis for technology forecasting Zan Wang Y.C. Tsim W.S. Yeung K.C. Chan Jinlan Liu Ingeniería Bibliometric analysis technology forecasting latent semantic analysis probabilistic latent semantic analysis Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA) has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA) which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency. Probabilistic Latent Semantic Analyses (PLSA) in Bibliometric Analysis for Technology Forecasting 2007 artículo científico 0718-2724 https://www.redalyc.org/articulo.oa?id=84720103 en http://www.redalyc.org/revista.oa?id=847 Journal of Technology Management & Innovation application/pdf Universidad Alberto Hurtado Journal of Technology Management & Innovation (Chile) Num.1 Vol.2
title Probabilistic latent semantic analyses (plsa) in bibliometric analysis for technology forecasting
topic Ingeniería
Bibliometric analysis
technology forecasting
latent semantic analysis
probabilistic latent semantic analysis
url https://www.redalyc.org/articulo.oa?id=84720103