Motivated by the commonly used faceted search interface in e-commerce, this paper investigates interactive relevance feedback mechanism based on faceted document metadata. In this...
Blog post opinion retrieval aims at finding blog posts that are relevant and opinionated about a user’s query. In this paper we propose a simple probabilistic model for assigni...
We build a probabilistic model to identify implicit local intent queries, and leverage user’s physical location to improve Web search results for these queries. Evaluation on co...
In this paper, we present a novel near-duplicate document detection method that can easily be tuned for a particular domain. Our method represents each document as a real-valued s...
Hannaneh Hajishirzi, Wen-tau Yih, Aleksander Kolcz
Effective learning in multi-label classification (MLC) requires an ate level of abstraction for representing the relationship between each instance and multiple categories. Curren...
Google Scholar allows researchers to search through a free and extensive source of information on scientific publications. In this paper we show that within the limited context o...
Traditional retrieval evaluation uses explicit relevance judgments which are expensive to collect. Relevance assessments inferred from implicit feedback such as click-through data...
Katja Hofmann, Bouke Huurnink, Marc Bron, Maarten ...
As a principled approach to capturing semantic relations of words in information retrieval, statistical translation models have been shown to outperform simple document language m...
Interleaving experiments are an attractive methodology for evaluating retrieval functions through implicit feedback. Designed as a blind and unbiased test for eliciting a preferen...
Yisong Yue, Yue Gao, Olivier Chapelle, Ya Zhang, T...