Clustering web search engine results for ambiguous keyword searches poses unique challenges. First, we show that one cannot readily import the frequency based feature ranking to c...
Due to the enormous size of the web and low precision of user queries, finding the right information from the web can be difficult if not impossible. One approach that tries to ...
In traditional text clustering methods, documents are represented as "bags of words" without considering the semantic information of each document. For instance, if two ...
Xiaohua Hu, Xiaodan Zhang, Caimei Lu, E. K. Park, ...
The growing amount of online news posted on the WWW demands new algorithms that support topic detection, search, and navigation of news documents. This work presents an algorithm f...
In this paper, we propose an information retrieval model called Latent Interest Semantic Map (LISM), which features retrieval composed of both Collaborative Filtering(CF) and Prob...