DocumentCode :
2198668
Title :
Greedy-Algorithm of KSORD Supporting Multi-language Phrase Recognition
Author :
Li, Peng ; Zhu, Qing ; Tian, Chao ; Wang, Shan
Author_Institution :
Key Lab. of Data Eng. & Knowledge Eng. Sch. of Inf., Renmin Univ. of China, Beijing
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
205
Lastpage :
209
Abstract :
With the rapid development of information retrieval technology and daily increasing information in the Internet, common users can retrieve many text-based database and get part of the information through the search engines such as Google, and Baidu. However, there is a great amount of data contained in the background relational database of web pages. So there are many researches focusing on the search in these relational database with keywords, compared with these researches, our algorithms are mainly based on bags using the greedy algorithms and supporting the phrase recognition by utilizing multiple dictionaries. We make a comparison between our algorithm and the existing ones. The experiment results shows that our algorithm owns not only the feature of effectiveness but also the feature of efficiency.
Keywords :
Internet; computational linguistics; data structures; dictionaries; greedy algorithms; information retrieval; natural language processing; relational databases; search engines; text analysis; Internet; Web page; data structure; greedy algorithm; information retrieval technology; multilanguage phrase recognition; multiple dictionary; relational database; search engine; text-based database; Chaos; Data engineering; Data structures; Dictionaries; Information retrieval; Internet; Knowledge engineering; Laboratories; Relational databases; Search engines; greedy algorithm; keyword search; relational database;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Theory and Engineering, 2008. ICACTE '08. International Conference on
Conference_Location :
Phuket
Print_ISBN :
978-0-7695-3489-3
Type :
conf
DOI :
10.1109/ICACTE.2008.38
Filename :
4736951
Link To Document :
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