Combining compound and single terms under language model framework

International audienceMost existing Information Retrieval model including probabilistic and vector space models are based on the term independence hypothesis. To go beyond this assumption and thereby capture the semantics of document and query more accurately, several works have incorporated phrases or other syntactic information in IR, such attempts have shown slight benefit, at best. Particularly in language modeling approaches this extension is achieved through the use of the bigram or n-gram models. However, in these models all bigrams/n-grams are considered and weighted uniformly. In this paper we introduce a new approach to select and weight relevant n-grams associated with a document. Experimental results on three TREC test collections showed an improvement over three strongest state-of-the-art model baselines, which are the original unigram language model, the Markov Random Field model, and the positional language model

Event program

UNLV Undergraduates from all departments, programs and colleges participated in a campus-wide symposium on April 16, 2011. Undergraduate posters from all disciplines and also oral presentations of research activities, readings and other creative endeavors were exhibited throughout the festival

The Trail, 1957-05-14

https://soundideas.pugetsound.edu/thetrail_all/1749/thumbnail.jp

Border Security: Understanding Threats at U.S. Borders

[Excerpt] The United States confronts a wide array of threats at U.S. borders, ranging from terrorists who may have weapons of mass destruction, to transnational criminals smuggling drugs or counterfeit goods, to unauthorized migrants intending to live and work in the United States. Given this diversity of threats, how may Congress and the Department of Homeland Security (DHS) set border security priorities and allocate scarce enforcement resources? In general, DHS’s answer to this question is organized around risk management, a process that involves risk assessment and the allocation of resources based on a cost-benefit analysis. This report focuses on the first part of this process by identifying border threats and describing a framework for understanding risks at U.S. borders. DHS employs models to classify threats as relatively high- or low-risk for certain planning and budgeting exercises and to implement certain border security programs. Members of Congress may wish to use similar models to evaluate the costs and benefits of potential border security policies and to allocate border enforcement resources. This report discusses some of the issues involved in modeling border-related threats