Titlebook: Operations Research Proceedings 1998; Selected Papers of t Peter Kall,Hans-Jakob Lüthi Conference proceedings 1999 Springer-Verlag Berlin H

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Abdul-Razak Alhassan,Mamudu Abunga Akuduguis paper presents some experiments on detecting and clustering similar sentences of texts in Brazilian Portuguese. We propose an evalution framework based on an incremental and unsupervised clustering method which is combined with statistical similarity metrics to measure the semantic distance betwe

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Was bringt mich als Führungskraft weiter?nage these data stream will play a very important role in the development of next-generation intelligent vehicular networks. Data stream classification problem poses many new challenges to the data mining area. One of the most basic challenges is how to make a tradeoff between data stream generating

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D. Riegelerfen empirische Fragen auf, von denen nachfolgend einige zur Diskussion gestellt werden. Bei den in besonderem Mass betroffenen Schülergruppen handelt es sich zum einen um die jungen ., die sich durch ihre Auseinandersetzung mit der Vereinbarkeitsproblematik von Beruf und Familie sowie aufgrund ihr

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J. Hoffmann-Jørgensen brings with it uncertainty and additional complexity. Severe turbulence is often regarded as making strategic action impossible. In this context, Boisot and others argue that extreme turbulence can be dealt with if the strategies designed and implemented are such that they can absorb complexity, an

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Society of Fire Protection Engineerss cycle and seasonal variations in reproductive activity. More recently the contribution of circadian rhythms to the’organization of longer rhythms has been explored. We became interested in this general topic after reading the report of Hansen and Södersten of a diurnal rhythm in the levels of lord

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Exploring Performance of Instance Selection Methods in Text Sentiment Classification,ne major problem encountered in these areas is overwhelming amount of data available. Hence, instance selection and feature selection become two essential tasks for achieving scalability in machine learning based sentiment classification. Instance selection is a data reduction technique which aims t

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