Title :
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
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;
Conference_Titel :
Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on
Conference_Location :
Fuzhou
Print_ISBN :
978-1-4799-2829-3
DOI :
10.1109/CLOUDCOM-ASIA.2013.102
