In this poster we propose a granular approach for presenting web search results. Sentences, taken from the top documents, are used as fine-grained representations of document cont...
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Incorporating features extracted from clickthrough data (called clickthrough features) has been demonstrated to significantly improve the performance of ranking models for Web sea...
Spam pages on the web use various techniques to artificially achieve high rankings in search engine results. Human experts can do a good job of identifying spam pages and pages wh...
This paper presents WordRank, a new page ranking system, which exploits similarity between interconnected pages. WordRank introduces the model of the ‘biased surfer’ which is ...