DocumentCode :
3739297
Title :
Matrix Plane Model: A Novel Measure of Word Co-occurrence and Application on Semantic Relatedness
Author :
Ji Qi;Yukio Ohsawa
Author_Institution :
Dept. of Syst. Innovation Sch. of Eng., Univ. of Tokyo Tokyo, Tokyo, Japan
fYear :
2015
Firstpage :
1246
Lastpage :
1253
Abstract :
Word co-occurrence measures co-occurring strength between words in texts. Most of the previous measures use a pre-decided context window to define co-occurrence of words. This size is decided from experience, and it is fixed during the whole process of measure. However, this is not ideal because appropriate window size can be different even in two adjacent sentences of a text. This paper provides a novel model called Matrix Plane Model (MPM), which can capture the best-fit window size dynamically and automatically. Also, we set up an experiment to compare MPM with some widely used measures by applying to semantic relatedness measures. The results show that our approach makes significant improvement in performance of semantic relatedness measures.
Keywords :
"Semantics","Context","Size measurement","Mathematical model","Probability","Conferences"
Publisher :
ieee
Conference_Titel :
Data Mining Workshop (ICDMW), 2015 IEEE International Conference on
Electronic_ISBN :
2375-9259
Type :
conf
DOI :
10.1109/ICDMW.2015.97
Filename :
7395811
Link To Document :
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