A Comparison of Methods for the Automatic Identification of Locations in Wikipedia

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A Comparison of Methods for the Automatic Identification of Locations in Wikipedia
Authors
Davide Buscaldi
Paolo Rosso
Publication date
2007
DOI
10.1145/1316948.1316971
Links
Original

A Comparison of Methods for the Automatic Identification of Locations in Wikipedia - scientific work related to Wikipedia quality published in 2007, written by Davide Buscaldi and Paolo Rosso.

Overview

In this paper authors compare two methods for the automatic identification of geographical articles in encyclopedic resources such as Wikipedia. The methods are a WordNet-based method that uses a set of keywords related to geographical places, and a multinomial Naive Bayes classificator, trained over a randomly selected subset of the English Wikipedia. This task may be included into the broader task of Named Entity classification, a well-known problem in the field of Natural Language Processing. The experiments were carried out considering both the full text of the articles and only the definition of the entity being described in the article. The obtained results show that the information contained in the page templates and the category labels is more useful than the text of the articles.

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Wikipedia Quality

Buscaldi, Davide; Rosso, Paolo. (2007). "[[A Comparison of Methods for the Automatic Identification of Locations in Wikipedia]]".DOI: 10.1145/1316948.1316971.

English Wikipedia

{{cite journal |last1=Buscaldi |first1=Davide |last2=Rosso |first2=Paolo |title=A Comparison of Methods for the Automatic Identification of Locations in Wikipedia |date=2007 |doi=10.1145/1316948.1316971 |url=https://wikipediaquality.com/wiki/A_Comparison_of_Methods_for_the_Automatic_Identification_of_Locations_in_Wikipedia}}

HTML

Buscaldi, Davide; Rosso, Paolo. (2007). &quot;<a href="https://wikipediaquality.com/wiki/A_Comparison_of_Methods_for_the_Automatic_Identification_of_Locations_in_Wikipedia">A Comparison of Methods for the Automatic Identification of Locations in Wikipedia</a>&quot;.DOI: 10.1145/1316948.1316971.