We address the task of learning rankings of documents from search engine logs of user behavior. Previous work on this problem has relied on passively collected clickthrough data. ...
Users’ past search behaviour provides a rich context that an information retrieval system can use to tailor its search results to suit an individual’s or a community’s infor...
PageRank is known to be an efficient metric for computing general document importance in the Web. While commonly used as a one-size-fits-all measure, the ability to produce topica...
Tables are ubiquitous. Unfortunately, no search engine supports table search. In this paper, we propose a novel table specific searching engine, TableSeer, to facilitate the table...
Latent semantic indexing (LSI) is a well-known unsupervised approach for dimensionality reduction in information retrieval. However if the output information (i.e. category labels...