TY - GEN
T1 - A fast tree-based search algorithm for cluster search engine
AU - Tsai, Chun Wei
AU - Huang, Ko Wei
AU - Chiang, Ming Chao
AU - Yang, Chu Sing
PY - 2009/12/1
Y1 - 2009/12/1
N2 - In this paper, we present an Intelligent Cluster Search Engine System, called ICSE. This system is motivated by the observation that traditional search engines present to the users a set of non-classified web pages based on its ranking mechanism, and the unfortunate results are that they usually can not satisfy the need of users. For this reason, ICSE provides to the user a set taxonomic web pages in response to a user's query, and thus it would greatly help the users filter out irrelevant or redundant information. The proposed system can be divided into two parts. The first is the knowledge base constructed by Open Directory Project and Yahoo! Directory. The second is the fast clustering algorithm described herein for clustering the web pages. In addition, in response to a user's query, the proposed system will first send the query to a meta-search engine. Then, it will create a clustered document set using the given knowledge base and the clustering algorithm of ICSE. Our simulation result showed that the proposed system can enhance the relevance and coverage of the search results that the users need compared with traditional search engines.
AB - In this paper, we present an Intelligent Cluster Search Engine System, called ICSE. This system is motivated by the observation that traditional search engines present to the users a set of non-classified web pages based on its ranking mechanism, and the unfortunate results are that they usually can not satisfy the need of users. For this reason, ICSE provides to the user a set taxonomic web pages in response to a user's query, and thus it would greatly help the users filter out irrelevant or redundant information. The proposed system can be divided into two parts. The first is the knowledge base constructed by Open Directory Project and Yahoo! Directory. The second is the fast clustering algorithm described herein for clustering the web pages. In addition, in response to a user's query, the proposed system will first send the query to a meta-search engine. Then, it will create a clustered document set using the given knowledge base and the clustering algorithm of ICSE. Our simulation result showed that the proposed system can enhance the relevance and coverage of the search results that the users need compared with traditional search engines.
UR - http://www.scopus.com/inward/record.url?scp=74849083086&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=74849083086&partnerID=8YFLogxK
U2 - 10.1109/ICSMC.2009.5346100
DO - 10.1109/ICSMC.2009.5346100
M3 - Conference contribution
AN - SCOPUS:74849083086
SN - 9781424427949
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 1603
EP - 1608
BT - Proceedings 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009
T2 - 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009
Y2 - 11 October 2009 through 14 October 2009
ER -