We address the problem of clustering the refinements of a user search query. The clusters computed by our proposed algorithm can be used to improve the selection and placement of the query suggestions proposed by a search engine, and can also serve to summarize the different aspects of information relevant to the original user query. Our algorithm clusters… (More)
Transmission of infectious diseases, propagation of information, and spread of ideas and influence through social networks are all examples of diffusion. In such cases we say that a contagion spreads through the network, a process that can be modeled by a cascade graph. Studying cascades and network diffusion is challenging due to missing data. Even a… (More)
Current speech synthesis technology is difficult to understand in everyday noise situations. Although there is a significant body of work on how humans modify their speech in noise, the results have yet to be implemented in a synthesizer. Algorithms capable of processing and incorporating these modifications may lead to improved speech intelligibility of… (More)
This paper uncovers a new phenomenon in web search that we call domain bias --- a user's propensity to believe that a page is more relevant just because it comes from a particular domain. We provide evidence of the existence of domain bias in click activity as well as in human judgments via a comprehensive collection of experiments. We begin by studying the… (More)
Analysis of a comprehensive set of features extracted from blogs for prediction of movie sales is presented. We use correlation, clustering and time-series analysis to study which features are best predictors.
Why running a startup is a lot like building a research lab.