Abstract
Recent years have witnessed an explosion in the availability of news articles on the World Wide Web. In addition, organizing the results of a news search facilitates the user(s) in overviewing the returned news. In this work, we have focused on the label-based clustering approaches for news meta-search engines, and which clusters news articles based on their topics. Furthermore, our engine for NEws meta-Search REsult Clustering (NeSReC) is implemented along. NeSReC takes queries from the users and collect the snippets of news which are retrieved by The Altavista News Search Engine for the queries. Afterwards, it performs the hierarchical clustering and labeling based on news snippets in a considerably tiny slot of time. © 2007 Springer.
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CITATION STYLE
Sayyadi, H., Salehi, S., & Abolhassani, H. (2007). NeSReC: A news meta-search engines result clustering tool. In Advances and Innovations in Systems, Computing Sciences and Software Engineering (pp. 173–178). https://doi.org/10.1007/978-1-4020-6264-3_31
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