Difference between revisions of "Semantic Tagging Using Topic Models Exploiting Wikipedia Category Network"
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| + | | title = Semantic Tagging Using Topic Models Exploiting Wikipedia Category Network | ||
| + | | date = 2016 | ||
| + | | authors = [[Mehdi Allahyari]]<br />[[Krys J. Kochut]] | ||
| + | | doi = 10.1109/ICSC.2016.34 | ||
| + | | link = | ||
| + | }} | ||
'''Semantic Tagging Using Topic Models Exploiting Wikipedia Category Network''' - scientific work related to [[Wikipedia quality]] published in 2016, written by [[Mehdi Allahyari]] and [[Krys J. Kochut]]. | '''Semantic Tagging Using Topic Models Exploiting Wikipedia Category Network''' - scientific work related to [[Wikipedia quality]] published in 2016, written by [[Mehdi Allahyari]] and [[Krys J. Kochut]]. | ||
== Overview == | == Overview == | ||
In this paper authors propose a probabilistic topic model that incorporates [[DBpedia]] knowledge into the topic model for tagging Web pages and online documents with topics discovered in them. Authors method is based on integration of the DBpedia hierarchical category network with statistical topic models where DBpedia [[categories]] are considered as topics. Authors have conducted extensive experiments on two different datasets to demonstrate the effectiveness of method. | In this paper authors propose a probabilistic topic model that incorporates [[DBpedia]] knowledge into the topic model for tagging Web pages and online documents with topics discovered in them. Authors method is based on integration of the DBpedia hierarchical category network with statistical topic models where DBpedia [[categories]] are considered as topics. Authors have conducted extensive experiments on two different datasets to demonstrate the effectiveness of method. | ||
Revision as of 08:44, 22 October 2020
Authors | Mehdi Allahyari Krys J. Kochut |
|---|---|
Publication date | 2016 |
DOI | 10.1109/ICSC.2016.34 |
Links |
Semantic Tagging Using Topic Models Exploiting Wikipedia Category Network - scientific work related to Wikipedia quality published in 2016, written by Mehdi Allahyari and Krys J. Kochut.
Overview
In this paper authors propose a probabilistic topic model that incorporates DBpedia knowledge into the topic model for tagging Web pages and online documents with topics discovered in them. Authors method is based on integration of the DBpedia hierarchical category network with statistical topic models where DBpedia categories are considered as topics. Authors have conducted extensive experiments on two different datasets to demonstrate the effectiveness of method.
