Difference between revisions of "Tsdw: Two-Stage Word Sense Disambiguation Using Wikipedia"
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| + | | title = Tsdw: Two-Stage Word Sense Disambiguation Using Wikipedia | ||
| + | | date = 2013 | ||
| + | | authors = [[Chenliang Li]]<br />[[Aixin Sun]]<br />[[Anwitaman Datta]] | ||
| + | | doi = 10.1002/asi.22829 | ||
| + | | link = http://onlinelibrary.wiley.com/doi/10.1002/asi.22829/full | ||
| + | }} | ||
'''Tsdw: Two-Stage Word Sense Disambiguation Using Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Chenliang Li]], [[Aixin Sun]] and [[Anwitaman Datta]]. | '''Tsdw: Two-Stage Word Sense Disambiguation Using Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Chenliang Li]], [[Aixin Sun]] and [[Anwitaman Datta]]. | ||
== Overview == | == Overview == | ||
The [[semantic knowledge]] of [[Wikipedia]] has proved to be useful for many tasks, for example, [[named entity]] disambiguation. Among these applications, the task of identifying the word sense based on Wikipedia is a crucial component because the output of this component is often used in subsequent tasks. In this article, authors present a two-stage framework (called TSDW) for word sense disambiguation using knowledge latent in Wikipedia. The disambiguation of a given phrase is applied through a two-stage disambiguation process: (a) The first-stage disambiguation explores the contextual [[semantic information]], where the noisy information is pruned for better effectiveness and efficiency; and (b) the second-stage disambiguation explores the disambiguated phrases of high confidence from the first stage to achieve better redisambiguation decisions for the phrases that are difficult to disambiguate in the first stage. Moreover, existing studies have addressed the disambiguation problem for English text only. Considering the popular usage of Wikipedia in [[different language]]s, authors study the performance of TSDW and the existing state-of-the-art approaches over both English and Traditional Chinese articles. The experimental results show that TSDW generalizes well to different semantic [[relatedness]] [[measures]] and text in different languages. More important, TSDW significantly outperforms the state-of-the-art approaches with both better effectiveness and efficiency. | The [[semantic knowledge]] of [[Wikipedia]] has proved to be useful for many tasks, for example, [[named entity]] disambiguation. Among these applications, the task of identifying the word sense based on Wikipedia is a crucial component because the output of this component is often used in subsequent tasks. In this article, authors present a two-stage framework (called TSDW) for word sense disambiguation using knowledge latent in Wikipedia. The disambiguation of a given phrase is applied through a two-stage disambiguation process: (a) The first-stage disambiguation explores the contextual [[semantic information]], where the noisy information is pruned for better effectiveness and efficiency; and (b) the second-stage disambiguation explores the disambiguated phrases of high confidence from the first stage to achieve better redisambiguation decisions for the phrases that are difficult to disambiguate in the first stage. Moreover, existing studies have addressed the disambiguation problem for English text only. Considering the popular usage of Wikipedia in [[different language]]s, authors study the performance of TSDW and the existing state-of-the-art approaches over both English and Traditional Chinese articles. The experimental results show that TSDW generalizes well to different semantic [[relatedness]] [[measures]] and text in different languages. More important, TSDW significantly outperforms the state-of-the-art approaches with both better effectiveness and efficiency. | ||
Revision as of 08:07, 22 June 2020
Authors | Chenliang Li Aixin Sun Anwitaman Datta |
|---|---|
Publication date | 2013 |
DOI | 10.1002/asi.22829 |
Links | Original |
Tsdw: Two-Stage Word Sense Disambiguation Using Wikipedia - scientific work related to Wikipedia quality published in 2013, written by Chenliang Li, Aixin Sun and Anwitaman Datta.
Overview
The semantic knowledge of Wikipedia has proved to be useful for many tasks, for example, named entity disambiguation. Among these applications, the task of identifying the word sense based on Wikipedia is a crucial component because the output of this component is often used in subsequent tasks. In this article, authors present a two-stage framework (called TSDW) for word sense disambiguation using knowledge latent in Wikipedia. The disambiguation of a given phrase is applied through a two-stage disambiguation process: (a) The first-stage disambiguation explores the contextual semantic information, where the noisy information is pruned for better effectiveness and efficiency; and (b) the second-stage disambiguation explores the disambiguated phrases of high confidence from the first stage to achieve better redisambiguation decisions for the phrases that are difficult to disambiguate in the first stage. Moreover, existing studies have addressed the disambiguation problem for English text only. Considering the popular usage of Wikipedia in different languages, authors study the performance of TSDW and the existing state-of-the-art approaches over both English and Traditional Chinese articles. The experimental results show that TSDW generalizes well to different semantic relatedness measures and text in different languages. More important, TSDW significantly outperforms the state-of-the-art approaches with both better effectiveness and efficiency.
