Abstract. This paper describes our participation in the TREC 2010 Blog Track. For the Top Stories Identification Task, we explore the relationship among news events, news stories and blog posts. We first extract important news events from the TRC2 corpus using a probabilistic mixture model. Then

Abstract. This paper describes our participation in the TREC 2009 Blog Track. Our system consists of the query likelihood component and the news headline prior component, based on the language model framework. For the query likelihood, we propose several approaches to estimate the query language model and the news headline language model. We also suggest two approaches to choose the 10 supporting relevant posts: Feed-Based Selection and Cluster-Based Selection. Furthermore, we propose two criteria to estimate the news headline prior for a given day. Experimental results show that using the prior significantly improves the performance of the task. 1

The term Linked Data refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions- the Web of Data. In this article we present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. We describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

A unified quantitative approach to modeling subjects ' identification and categorization of multidimensional perceptual stimuli is proposed and tested. Two subjects identified and categorized the same set of perceptually confusable stimuli varying on separable dimensions. The identification

cultivation.of individual microbial cells without Phylogenetic identification and in situ detection

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A general theory of domain identification is used to describe achievement barriers still faced by women in advanced quantitative areas and by African Americans in school. The theory assumes that sustained school success requires identification with school and its subdomains; that societal pressures

effects of a monetary policy shock in the sense that inference is robust across a large subset of the identification schemes that have been considered in the literature. We document the nature of this agreement as

categorization tasks. We present results comparing the performance of BoosTexter and a number of other text-categorizationalgorithms on a variety of tasks. We conclude by describing the application of our system to automatic call-type identification from unconstrained spoken customer responses.

This paper characterizes the dynamic effects of shocks in government spending and taxes on U. S. activity in the postwar period. It does so by using a mixed structural VAR/event study approach. Identification is achieved by using institutional information about the tax and transfer systems