Title :
An Efficient Algorithm for Clustering Search Engine Results
Author :
Zhang, Hui ; Pang, Bin ; Xie, Ke ; Wu, Hui
Author_Institution :
National Lab. of Software Dev. Environ., Beihang Univ., Beijing
Abstract :
With the increasing number of Web documents in the Internet, the most popular keyword-matching-based search engines, such as Google, often return a long list of search results ranked based on their relevance and importance to the query. To cluster the search engine results can help users find the results in several clustered collections, so it is easy to locate the valuable search results that the users really needed. In this paper, we propose a new key-feature clustering (KFC) algorithm which firstly extracts the significant keywords from the results as key features and cluster them, then clusters the documents based on these clustered key features. At last, the paper presents and analyzes the results from experiments we conducted to test and validate the algorithm
Keywords :
Internet; document handling; pattern clustering; relevance feedback; search engines; Google; Internet; Web documents; key-feature clustering; keyword matching; search engine result clustering; Algorithm design and analysis; Clustering algorithms; Flowcharts; Frequency; Internet; Programming; Search engines; Software algorithms; Testing; Web pages;
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
DOI :
10.1109/ICCIAS.2006.295296