Suffix Tree Clustering with Named Entity Recognition

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).

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