This paper proposes relationship discovery models using opinions mined from the Web instead of only conventional collocations. Web opinion mining extracts subjective information f...
In this paper we present a new document representation model based on implicit user feedback obtained from search engine queries. The main objective of this model is to achieve be...
Our research explores the possibilities for factoring culture into user models, working towards cultural adaptivity in the semantic web. The aim is to represent the user’s positi...
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
Personalized web search is a promising way to improve search quality by customizing search results for people with individual information goals. However, users are uncomfortable w...