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The Markov Random Walk model has been recently exploited for multi-document summarization by making use of the link relationships between sentences in the document set, under the ...
Determining semantic relatedness between words or concepts is a fundamental process to many Natural Language Processing applications. Approaches for this task typically make use o...
We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...
Traditional web link-based ranking schemes use a single score to measure a page’s authority without concern of the community from which that authority is derived. As a result, a...
In previous work, we developed the Illum-PF-MT, which is the PFMT idea applied to the problem of tracking temporally and spatially varying illumination change. In many practical p...
Collaborative filtering is the most popular approach to build recommender systems and has been successfully employed in many applications. However, it cannot make recommendations ...