Research on adaptive classification algorithm based on non-segment and classified-centre-vector. (1st January 2013)

• Record Type: Journal Article
• Authors: Gao, Kai; Wang, Xiang; Wang, Wei
• Is Part Of: International journal of intelligent information and database systems. Volume 7:Number 6(2013)
• Page Start: 550
• Page End: 566
• Publication Date: 2013-01-01
• Subjects: classification -- classified-centre-vector -- non-segment -- bias revising; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

Classification is essential to many web applications such as focused crawling, search engine, recommendation, content filter, knowledge discovery, etc. Although traditional classification algorithms have many virtues, the unstructured and big web data application presents challenges to these traditional algorithms. Moreover, the traditional segmentation processing usually needs more time and a complete lexicon. This work focuses on an interesting and promising approach that may enhance the classification performance of web and big data applications. Based on the non-segment and the classified-centre-vector, the proposed algorithm can meet the request on big data classifications. By using positive and negative modification, it can revise the potential data bias. The experimental results and the analysis show the feasibility of this approach.