We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
We present BAYESUM (for "Bayesian summarization"), a model for sentence extraction in query-focused summarization. BAYESUM leverages the common case in which multiple do...
The World Wide Web is a large, heterogeneous, distributedcollectionof documents connected by hypertext links. The most common technologycurrently used for searching the Web depend...
Alberto O. Mendelzon, George A. Mihaila, Tova Milo
Continuing innovations in information and communication technologies offer powerful tools for building digital government but, at the same time, in many environments they have lea...