We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...
Many industries experience an explosion in digital content. This explosion of electronic documents, along with new regulations and document retention rules, sets new requirements f...
In this paper we present a method for reformulating the Recommender Systems problem in an Information Retrieval one. In our tests we have a dataset of users who give ratings for s...
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...