Suffix Tree Clustering with Named Entity Recognition

Author

Jiwei Zhang ; Qiuyue Dang ; Yueming Lu ; Songlin Sun

Author_Institution

Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2013

fDate

16-19 Dec. 2013

Firstpage

549

Lastpage

556

Abstract

The news searching is challengeable in providing web users with clear and readable lists of news reports. This paper proposes the Suffix Tree Clustering with Named Entity Recognition (STC-NER). STC-NER is supposed to cluster news searching results returned by the search engine. STC-NER uses the snippets returned from the searching results and then derives patterned information by means of named entity recognition. STC-NER makes a great contribute to the reduction of storage as well as the time complexity. Experiments show that STC-NER has a better performance in precision and efficiency than the traditional Suffix Tree Clustering (STC).

Keywords

pattern clustering; storage management; text analysis; STC-NER; Web users; news searching; search engine; snippets; storage reduction; suffix tree clustering with named entity recognition; text document clustering algorithm; Algorithm design and analysis; Clustering algorithms; Educational institutions; Organizations; Search engines; Tagging; Vectors; clustering; named entity recognition; news reports; suffix Tree;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on

Conference_Location

Fuzhou

Print_ISBN

978-1-4799-2829-3

Type

conf

DOI

10.1109/CLOUDCOM-ASIA.2013.102

Filename

6821048