Difference between revisions of "Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia"
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| + | | title = Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia | ||
| + | | date = 2006 | ||
| + | | authors = [[Yutaka Matsuo]]<br />[[Mitsuru Ishizuka]] | ||
| + | | link = http://www.miv.t.u-tokyo.ac.jp/papers/dat-IJCAI07-TextLinkWS.pdf | ||
| + | }} | ||
'''Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2006, written by [[Yutaka Matsuo]] and [[Mitsuru Ishizuka]]. | '''Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2006, written by [[Yutaka Matsuo]] and [[Mitsuru Ishizuka]]. | ||
== Overview == | == Overview == | ||
The exponential growth of [[Wikipedia]] recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and [[semantic information]] for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding. | The exponential growth of [[Wikipedia]] recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and [[semantic information]] for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding. | ||
Revision as of 22:50, 9 August 2019
Authors | Yutaka Matsuo Mitsuru Ishizuka |
|---|---|
Publication date | 2006 |
Links | Original |
Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia - scientific work related to Wikipedia quality published in 2006, written by Yutaka Matsuo and Mitsuru Ishizuka.
Overview
The exponential growth of Wikipedia recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and semantic information for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding.
