Graph based Ranked Answers for Keyword Graph Structure

Title
Graph based Ranked Answers for Keyword Graph Structure
Authors
이우기
Keywords
Intelligent Systems, Fuzzy Sets, Keyword Search, Rank, Graph.
Issue Date
2013
Publisher
NEW GENERATION COMPUTING
Series/Report no.
NEW GENERATION COMPUTING; vol.31 startpage 115 endpage 134
Abstract
Keyword query processing over graph structured data is beneficial across various real world applications. The basic unit, of search and retrieval, in keyword search over graph, is a structure (interconnection of nodes) that connects all the query keywords. This new answering paradigm, in contrast to single web page results given by search engines, brings forth new challenges for ranking. In this paper, we propose a simple but effective Fuzzy set theory based Ranking measure, called FRank. Fuzzy sets acknowledge the contribution of each individual query keyword, discretely, to enumerate node relevance. A novel aggregation operator is defined, to combine the content relevance based fuzzy sets and, compute query dependent edge weights. The final rank, of an answer, is computed by non-monotonic addition of edge weights, as per their relevance to keyword query. FRank evaluates each answer based on the distribution of query keywords and structural connectivity between those keywords. An extensive empirical analysis shows superior performance by our proposed ranking measure as compared to the ranking measures adopted by current approaches in the literature.
URI
http://dspace.inha.ac.kr/handle/10505/31983
ISSN
0288-3635
Appears in Collections:
College of Engineering(공과대학) > Industrial Engineering (산업경영공학) > Journal Papers, Reports(산업공학 논문, 보고서)
Files in This Item:
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