A Novel Approach to Automatic Gazetteer Generation Using Wikipedia

From Wikipedia Quality
Revision as of 23:13, 21 March 2021 by Elana (talk | contribs) (Embed)
Jump to: navigation, search


A Novel Approach to Automatic Gazetteer Generation Using Wikipedia
Authors
Ziqi Zhang
José Iria
Publication date
2009
DOI
10.3115/1699765.1699766
Links
Original

A Novel Approach to Automatic Gazetteer Generation Using Wikipedia - scientific work related to Wikipedia quality published in 2009, written by Ziqi Zhang and José Iria.

Overview

Gazetteers or entity dictionaries are important knowledge resources for solving a wide range of NLP problems, such as entity extraction. Authors introduce a novel method to automatically generate gazetteers from seed lists using an external knowledge resource, the Wikipedia. Unlike previous methods, method exploits the rich content and various structural elements of Wikipedia, and does not rely on language- or domain-specific knowledge. Furthermore, applying the extended gazetteers to an entity extraction task in a scientific domain, authors empirically observed a significant improvement in system accuracy when compared with those using seed gazetteers.

Embed

Wikipedia Quality

Zhang, Ziqi; Iria, José. (2009). "[[A Novel Approach to Automatic Gazetteer Generation Using Wikipedia]]". Association for Computational Linguistics. DOI: 10.3115/1699765.1699766.

English Wikipedia

{{cite journal |last1=Zhang |first1=Ziqi |last2=Iria |first2=José |title=A Novel Approach to Automatic Gazetteer Generation Using Wikipedia |date=2009 |doi=10.3115/1699765.1699766 |url=https://wikipediaquality.com/wiki/A_Novel_Approach_to_Automatic_Gazetteer_Generation_Using_Wikipedia |journal=Association for Computational Linguistics}}

HTML

Zhang, Ziqi; Iria, José. (2009). &quot;<a href="https://wikipediaquality.com/wiki/A_Novel_Approach_to_Automatic_Gazetteer_Generation_Using_Wikipedia">A Novel Approach to Automatic Gazetteer Generation Using Wikipedia</a>&quot;. Association for Computational Linguistics. DOI: 10.3115/1699765.1699766.