A Wikipedia-Based Conceptual Keyword Expansion System and Its Application
Date Issued
2008
Date
2008
Author(s)
Yeh, Yang-Ting
Abstract
In this thesis, we propose a framework to generate semantic graphs by using collabora-tive knowledge as well as social network hidden behind Wikipedia, and the derived se-mantic graphs are then used to conduct semantic keyword expansion. Wikipedia is a web-based free encyclopedia that anyone can edit. In addition, Wikipedia keeps all ver-sions and contributors for each page, and therefore, we can collect the information of all contributors who have edited some specific concept page. As a result, we can form a bipartite graph between topics in Wikipedia and Wikipedia’s contributors. We then util-ize a novel weighting model to fold the bipartite graph into a topic only graph which we call semantic relatedness graph. A semantic relatedness graph is a WordNet liked net-work, in which the listed words have specific semantic meaning since we have identi-fied various entries of Wikipedia as concepts. Furthermore, the weights on edges con-necting words express the degree of semantic relatedness between words. We also pro-pose a mechanism to rate the nodes in a semantic graph and provide a ranking list for those users who are used to traditional recommendation systems on the basis of the proposed semantic word expansion system. A novel way to conduct image search is also suggested and demonstrated. Experiment results show that our system is flexible and useful. To the best of our knowledge, we are the first team to explicitly use Wikipedia’s social network to compute semantic relatedness and to apply the obtained semantic graphs for conducting image search.
Subjects
Social Network Analysis
Collaborative Knowledge
Semantic Relatedness Graph
Conceptual Keyword Expansion
Ranking
Image Search
Query Expansion
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-97-R95944012-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):2e60eaf3d1eae419125896c0a5e98286