Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of ...
Eugene Agichtein, Eric Brill, Susan T. Dumais, Rob...
We introduce in this paper a generalization of the widely used hidden Markov models (HMM's), which we name "structural hidden Markov models" (SHMM). Our approach is ...
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without takin...
Wayne Xin Zhao, Jing Jiang, Jing He, Dongdong Shan...
We propose novel spatio-temporal models to estimate clickthrough rates in the context of content recommendation. We track article CTR at a fixed location over time through a dynam...
Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...