In this paper we present a language independent approach for conflation that does not depend on predefined rules or prior knowledge in the target language. Different from prior studies on Arabic text that use pure n-gram models without any attempt for further enhancement on the basis of refined n-gram

This paper examines a conflation method based on the N-grams approach and evaluates its performance relative to the results achieved by other techniques such as Porter algorithm and successor variety stemming. In addition to that, an alternative way of enhancing the N-grams method, derived from

Abstract. This paper focuses on a comparative evaluation of a wide-range of text categorization methods, including previously published results on the Reuters corpus and new results of additional experiments. A controlled study using three classifiers, kNN, LLSF and WORD, was conducted to examine

in email, and character recognition errors in documents that come through OCR. Text categorization must work reliably on all input, and thus must tolerate some level of these kinds of problems. We describe here an N-gram-based approach to text categorization that is tolerant of textual errors. The system

by 200-300 of the largest singular vectors are then matched against user queries. We call this retrieval method Latent Semantic Indexing (LSI) because the subspace represents important associative relationships between terms and documents that are not evident in individual documents. LSI is a completely

, code mobility is generating a growing body of scientific literature and industrial developments. Nevertheless, the field is still characterized by the lack of a sound and comprehensive body of concepts and terms. As a consequence, it is rather difficult to understand, assess, and compare the existing

This dissertation is a defense of the hypothesis that the noun phrase is headed by afunctional element (i.e., \non-lexical " category) D, identi ed with the determiner. In this way, the structure of the noun phrase parallels that of the sentence, which is headed by In (ection), under assumptions now standard within the Government-Binding (GB) framework. The central empirical problem addressed is the question of the proper analysis of the so-called \Poss-ing " gerund in English. This construction possesses simultaneously many properties of sentences, and many properties of noun phrases. The problem of capturing this dual aspect of the Possing construction is heightened by current restrictive views of X-bar theory, which, in particular, rule out the obvious structure for Poss-ing, [NP NP VPing], by virtue of its exocentricity. Consideration of languages in which nouns, even the most basic concrete nouns, show agreement (AGR) with their possessors, points to an analysis

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There is a growing need for ad-hoc analysis of extremely large data sets, especially at internet companies where innovation critically depends on being able to analyze terabytes of data collected every day. Parallel database products, e.g., Teradata, offer a solution, but are usually prohibitively expensive at this scale. Besides, many of the people who analyze this data are entrenched procedural programmers, who find the declarative, SQL style to be unnatural. The success of the more procedural map-reduce programming model, and its associated scalable implementations on commodity hardware, is evidence of the above. However, the map-reduce paradigm is too low-level and rigid, and leads to a great deal of custom user code that is hard to maintain, and reuse. We describe a new language called Pig Latin that we have designed to fit in a sweet spot between the declarative style of SQL, and the low-level, procedural style of map-reduce. The accompanying system, Pig, is fully implemented, and compiles Pig Latin into physical plans that are executed over Hadoop, an open-source, map-reduce implementation. We give a few examples of how engineers at Yahoo! are using Pig to dramatically reduce the time required for the development and execution of their data analysis tasks, compared to using Hadoop directly. We also report on a novel debugging environment that comes integrated with Pig, that can lead to even higher productivity gains. Pig is an open-source, Apache-incubator project, and available for general use. 1.

El Salvador, Guatemala is a, study in black and white. On the left is a collection of extreme Marxist-Leninist groups led by what one diplomat calls “a pretty faceless bunch of people.’ ’ On the right is an entrenched elite that has dominated Central America’s most populous country since a CIA-backed coup deposed the reformist government of Col. Jacobo Arbenz Guzmán in 1954. Moderates of the political center. embattled but alive in E1 Salvador, have virtually disappeared in Guatemala-joining more than 30.000 victims of terror over the last tifteen vears. “The situation in Guatemala is much more serious than in EI Salvador, ” declares one Latin American diplomat. “The oligarchy is that much more reactionary. and the choices are far fewer. “ ‘Zero’: The Guatemalan oligarchs hated Jimmy Carter for cutting off U.S. military aid in 1977 to protest human-rights abuses-and the right-wingers hired marimba bands and set off firecrackers on the night Ronald Reagan was elected. They considered Reagan an ideological kinsman and believed they had a special