9,995 research outputs found

    Peak oil, geopolitics and the need for relocalization: will our magnificent obsession become our obsolete obsession?

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    This essay will look at the peak oil question, contemporary “oil geopolitics” and their effect not only on energy supplies, but also on transportation, agriculture and food supplies, and population distribution in the United States. While the war in Iraq forms a centerpiece in the geopolitical scene, Russia, China, and other nations will be discussed as well. This essay will also examine the inevitable relocalization which appears to be a necessary result

    Establishing Branch Libraries

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    published or submitted for publicatio

    Automatic Extraction of Subcategorization from Corpora

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    We describe a novel technique and implemented system for constructing a subcategorization dictionary from textual corpora. Each dictionary entry encodes the relative frequency of occurrence of a comprehensive set of subcategorization classes for English. An initial experiment, on a sample of 14 verbs which exhibit multiple complementation patterns, demonstrates that the technique achieves accuracy comparable to previous approaches, which are all limited to a highly restricted set of subcategorization classes. We also demonstrate that a subcategorization dictionary built with the system improves the accuracy of a parser by an appreciable amount.Comment: 8 pages; requires aclap.sty. To appear in ANLP-9

    Unsupervised induction of Arabic root and pattern lexicons using machine learning

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    We describe an approach to building a morphological analyser of Arabic by inducing a lexicon of root and pattern templates from an unannotated corpus. Using maximum entropy modelling, we capture orthographic features from surface words, and cluster the words based on the similarity of their possible roots or patterns. From these clusters, we extract root and pattern lexicons, which allows us to morphologically analyse words. Further enhancements are applied, adjusting for morpheme length and structure. Final root extraction accuracy of 87.2% is achieved. In contrast to previous work on unsupervised learning of Arabic morphology, our approach is applicable to naturally-written, unvowelled Arabic text

    Induction of root and pattern lexicon for unsupervised morphological analysis of Arabic

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    We propose an unsupervised approach to learning non-concatenative morphology, which we apply to induce a lexicon of Arabic roots and pattern templates. The approach is based on the idea that roots and patterns may be revealed through mutually recursive scoring based on hypothesized pattern and root frequencies. After a further iterative refinement stage, morphological analysis with the induced lexicon achieves a root identification accuracy of over 94%. Our approach differs from previous work on unsupervised learning of Arabic morphology in that it is applicable to naturally-written, unvowelled text

    Apportioning Development Effort in a Probabilistic LR Parsing System through Evaluation

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    We describe an implemented system for robust domain-independent syntactic parsing of English, using a unification-based grammar of part-of-speech and punctuation labels coupled with a probabilistic LR parser. We present evaluations of the system's performance along several different dimensions; these enable us to assess the contribution that each individual part is making to the success of the system as a whole, and thus prioritise the effort to be devoted to its further enhancement. Currently, the system is able to parse around 80% of sentences in a substantial corpus of general text containing a number of distinct genres. On a random sample of 250 such sentences the system has a mean crossing bracket rate of 0.71 and recall and precision of 83% and 84% respectively when evaluated against manually-disambiguated analyses.Comment: 10 pages, 1 Postscript figure. To Appear in Proceedings of the Conference on Empirical Methods in Natural Language Processing, University of Pennsylvania, May 199

    Weakly-supervised appraisal analysis

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    This article is concerned with the computational treatment of Appraisal, a Systemic Functional Linguistic theory of the types of language employed to communicate opinion in English. The theory considers aspects such as Attitude (how writers communicate their point of view), Engagement (how writers align themselves with respect to the opinions of others) and Graduation (how writers amplify or diminish their attitudes and engagements). To analyse text according to the theory we employ a weakly-supervised approach to text classification, which involves comparing the similarity of words with prototypical examples of classes. We evaluate the method's performance using a collection of book reviews annotated according to the Appraisal theory

    Reducing the federal deficit: approaches in some other countries

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    The United States is not the first advanced modern economy to face a serious federal budget challenge. A number of countries have seen their debt rise to unacceptable levels in recent decades, and they have taken steps to rein it in. We explore the approaches that Canada and the United Kingdom have used. Though there are important differences in approaches and countries, we draw five useful lessons for the reforms that may be proposed in the U.S. as it addresses its fiscal challenges.Debts, Public - Canada ; Deficit financing ; Debt - United States ; Debts, Public - United Kingdom
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