Difference between revisions of "Document Categorization Using Multilingual Associative Networks based on Wikipedia"
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| − | '''Document Categorization Using Multilingual Associative Networks based on Wikipedia''' - scientific work related to Wikipedia quality published in 2015, written by Niels Bloom, Mariët Theune and Franciska de Jong. | + | '''Document Categorization Using Multilingual Associative Networks based on Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[Niels Bloom]], [[Mariët Theune]] and [[Franciska de Jong]]. |
== Overview == | == Overview == | ||
| − | Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research authors combine monolingual associative networks based on Wikipedia to create a larger, multilingual associative network, using the cross-lingual connections between Wikipedia articles. Authors prove that such multilingual associative networks perform better than monolingual associative networks in tasks related to document categorization by comparing the results of both types of associative network on a multilingual dataset. | + | Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research authors combine monolingual associative networks based on [[Wikipedia]] to create a larger, [[multilingual]] associative network, using the [[cross-lingual]] connections between Wikipedia articles. Authors prove that such multilingual associative networks perform better than monolingual associative networks in tasks related to document categorization by comparing the results of both types of associative network on a multilingual dataset. |
Revision as of 06:11, 10 June 2019
Document Categorization Using Multilingual Associative Networks based on Wikipedia - scientific work related to Wikipedia quality published in 2015, written by Niels Bloom, Mariët Theune and Franciska de Jong.
Overview
Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research authors combine monolingual associative networks based on Wikipedia to create a larger, multilingual associative network, using the cross-lingual connections between Wikipedia articles. Authors prove that such multilingual associative networks perform better than monolingual associative networks in tasks related to document categorization by comparing the results of both types of associative network on a multilingual dataset.
