Paper Info
Title
Automatic Facet Extraction Based on Multidimensional Semantic Index
Abstract
Faceted search on web pages needs exact facets. However, it is difficult to extract facets exactly from web pages because the web pages are unstructured and lack of facet information. Therefore, facet extraction is a key to faceted search. This paper proposed a method of extracting facets automatically from unstructured web pages to improve the faceted search on web. The Multidimensional Semantic Index (MDSI) of web pages is constructed by mining all kinds of semantic relations among the words from web pages, which creates a semantic-rich index for web pages. In MDSI, the differently dimensional semantic indexes are bridged by mining the semantic mapping between them. Based on the MDSI of web pages, the facets are extracted by analyzing semantic mapping relations in MDSI. To validate the effect of the proposed method, two datasets are constructed and the experimental results show that the proposed method is feasible and comparatively precise.
Year
DOI
Venue
2012
10.1109/SKG.2012.22
SKG
Keywords
Field
DocType
facet information,web page mdsi,unstructured web pages,semantic mapping,semantic relation,multidimensional semantic index,web page mining,semantic-rich index,search problems,faceted search,feature extraction,facet extraction,web sites,unstructured web page,image retrieval,exact facet,facet search,semantic mapping relation,automatic facet extraction,data mining,web page,dimensional semantic index
Data mining,Web mining,Semantic search,Web page,Information retrieval,Semantic Web Stack,Faceted search,Computer science,Data Web,Semantic analytics,Social Semantic Web
Conference
ISBN
Citations 
PageRank 
978-1-4673-2561-5
0
0.34
References 
Authors
12
3
Name
Order
Citations
PageRank
Xiao Wei1525.18
Xiangfeng Luo21251124.38
Qing Li33222433.87