A New Hybrid Improved Method for Measuring Concept Semantic Similarity in WordNet

IAJIT
Archive
- Volume 20, 2023
  
  January 2023, No.1
  
  March 2023, No.2
- Volume 19, 2022
  
  January 2022, No.1
  
  March 2022, No.2
  
  May 2022, No. 3
  
  Special Issue 2022, No. 3A
  
  July 2022, No. 4
  
  September 2022, No. 5
  
  November 2022, No. 6
- Volume 18, 2021
  
  January 2021, No.1
  
  March 2021, No.2
  
  May 2021, No. 3
  
  Special Issue 2021, No. 3A
  
  July 2021, No. 4
  
  September 2021, No. 5
  
  November 2021, No. 6
- Volume 17, 2020
  
  January 2020, No.1
  
  March 2020, No. 2
  
  May 2020, No. 3
  
  July 2020, No. 4
  
  Special Issue 2020, No. 4A
  
  September 2020, No. 5
  
  November 2020, No. 6
- Volume 16, 2019
  
  January 2019, No.1
  
  March 2019, No. 2
  
  May 2019, No. 3
  
  Special Issue 2019, No. 3A
  
  July 2019, No. 4
  
  September 2019, No. 5
  
  November 2019, No. 6
- Volume 15, 2018
  
  January 2018, No.1
  
  March 2018, No. 2
  
  May 2018, No. 3
  
  Special Issue 2018, No. 3A
  
  July 2018, No. 4
  
  September 2018, No. 5
  
  November 2018, No. 6
- Volume 14, 2017
  
  January 2017, No.1
  
  March 2017, No. 2
  
  May 2017, No. 3
  
  July 2017, No. 4
  
  pecial Issue 2017, No. 4A
  
  September 2017, No 5
  
  November 2017, No. 6
- Volume 13, 2016
  
  January 2016. No.1
  
  March 2016, No. 2
  
  May 2016, No. 3
  
  July 2016, No.4
  
  September 2016, No.5
  
  November 2016, No.6
- Volume 12, 2015
  
  January 2015. No.1
  
  March 2015. No.2
  
  May 2015. No.3
  
  July 2015. No.4
  
  September 2015. No. 5
  
  November 2015. No. 6
  
  December 2015. No. 6A
- Volume 11, 2014
  
  January 2014, No.1
  
  March 2014, No.2
  
  May 2014, No.3
  
  July 2014, No.4
  
  November 2014, No.6
- Volume 10, 2013
  
  January 2013, No. 1
  
  March 2013, No.2
  
  May 2013, No. 3
  
  July 2013, No. 4
  
  November 2013, No. 6
- Volume 9, 2012
  
  January 2012, No. 1
  
  March 2012, No. 2
  
  May 2012, No. 3
  
  July 2012, No. 4
  
  September 2012, No. 5
  
  November 2012, No. 6
- Volume 8, 2011
  
  January 2011, No 1
  
  April 2011, No. 2
  
  July 2011, No. 3
  
  October 2011, No.4
- Volume 7, 2010
  
  October 2010, No. 4
  
  July 2010, No. 3
  
  April 2010, No. 2
  
  January 2010, No. 1
- Volume 6, 2009
  
  January 2009, No. 1
  
  April 2009, No. 2
  
  July 2009, No. 3
  
  October 2009, No. 4
  
  November 2009, No. 5
- Volume 5, 2008
  
  January 2008, No. 1
  
  April 2008, No.2
  
  July 2008, No. 3
  
  October 2008, No. 4
- Volume 4, 2007
  
  January 2007, No. 1
  
  April 2007, No. 2
  
  July 2007, No.3
  
  October 2007, No. 4
- Volume 3, 2006
  
  January 2006, No. 1
  
  April 2006, No. 2
  
  July 2006, No. 3
  
  October 2006, No. 4
- Volume 2, 2005
  
  January 2005, No. 1
  
  April 2005, No. 2
  
  July 2005, No. 3
  
  October 2005, No. 4
- Volume 1, 2003-2004
  
  July 2004, No. 2
  
  January 2004, No. 1
  
  July 2003, No. 0
About IAJIT
About CCIS
IAJIT Impact Factor

A New Hybrid Improved Method for Measuring Concept Semantic Similarity in WordNet

Written by Super User
Update: 30/06/2020

font size decrease font size increase font size
Print
Email
Rate this item
- 1
- 2
- 3
- 4
- 5
(0 votes)

A New Hybrid Improved Method for Measuring Concept Semantic Similarity in WordNet

Xiaogang Zhang, Shouqian Sun,and Kejun Zhang

College of Computer Science and Technology, Zhejiang University, Hangzhou, China

Abstract: Computing semantic similarity between concepts is an important issue in natural language processing, artificial intelligence, information retrieval and knowledge management. The measure of computing concept similarity is a fundament of semantic computation. In this paper, we analyze typical semantic similarity measures and note Wu and Palmer’s measure which does not distinguish the similarities between nodes from a node to different nodes of the same level. Then, we synthesize the advantages of measure of path-based and IC-based, and propose a new hybrid method for measuring semantic similarity. By testing on a fragment of WordNet hierarchical tree, the results demonstrate the proposed method accurately distinguishes the similarities between nodes from a node to different nodes of the same level and overcome the shortcoming of the Wu and Palmer’s measure.