We present a novel language-model-based approach to reranking search results; that is, reordering the documents in an initially retrieved list so as to improve precision at top ranks. Our model integrates whole-document information with that induced ...
In adversarial and noisy search settings as the Web, the document-query surface level similarity can be a highly misleading relevance signal. Thus, devising content-based relevance estimation (ranking) approaches becomes highly challenging. We address ...
Measuring inter-document similarity is one of the most essential steps in text document clustering. Traditional methods rely on representing text documents using the simple Bag-of-Words (BOW) model. A document is an organized structure consisting of ...
Association for Computing Machinery
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