Effective Techniques for Indonesian Text Retrieval

 
9783639021646: Effective Techniques for Indonesian Text Retrieval

In this thesis, we investigate information retrieval techniques for Indonesian. Stemming is the process of reducing morphological variants of a word to a common stem form. Although several stemming algorithms have been proposed for Indonesian, there is no consensus on which gives better performance. We empirically explore these stemming algorithms, propose novel extensions to the best algorithm, develop a new Indonesian stemmer, and show that these can improve stemming correctness. We propose a range of techniques to enhance the performance of Indonesian information retrieval. Our experiments show that many of these techniques can increase retrieval performance. We also address the problem of automatic creation of parallel corpora which are essential for cross-lingual information retrieval and other natural language processing tasks, including machine translation. We describe algorithms that we have developed to automatically identify parallel documents for Indonesian and English. We also investigate the applicability of our identification algorithms for other languages that use the Latin alphabet including German and French.

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About the Author:

Jelita finished her PhD from the RMIT University, Australia in 2007. Her research interest includes information retrieval (mono and cross-lingual), natural language processing, machine translation, and corpus construction. She currently works as a C/C++ software engineer.

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Asian, Jelita
ISBN 10: 3639021649 ISBN 13: 9783639021646
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Book Description Book Condition: New. Publisher/Verlag: VDM Verlag Dr. Müller | Indonesian Text Retrieval | In this thesis, we investigate information retrievaltechniques for Indonesian.Stemming is the process of reducing morphologicalvariants of a word to acommon stem form.Although several stemming algorithms have beenproposed for Indonesian,there is no consensus on which gives better performance.We empirically explore these stemming algorithms,propose novel extensions to the best algorithm, develop a new Indonesian stemmer, and show thatthese can improve stemming correctness.We propose a range of techniques to enhance theperformance of Indonesian information retrieval.Our experiments show that many of these techniquescan increase retrieval performance.We also address the problem of automatic creation ofparallel corpora which are essential forcross-lingual information retrieval and othernatural language processing tasks, including machinetranslation.We describe algorithms that we have developed toautomatically identify parallel documents forIndonesian and English.We also investigate the applicability of ouridentification algorithmsfor other languages that use the Latin alphabetincluding German and French. | Format: Paperback | Language/Sprache: english | 292 pp. Bookseller Inventory # K9783639021646

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Jelita Asian
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ISBN 10: 3639021649 ISBN 13: 9783639021646
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Book Description VDM Verlag Jun 2009, 2009. Taschenbuch. Book Condition: Neu. Neuware - In this thesis, we investigate information retrieval techniques for Indonesian. Stemming is the process of reducing morphological variants of a word to a common stem form. Although several stemming algorithms have been proposed for Indonesian, there is no consensus on which gives better performance. We empirically explore these stemming algorithms, propose novel extensions to the best algorithm, develop a new Indonesian stemmer, and show that these can improve stemming correctness. We propose a range of techniques to enhance the performance of Indonesian information retrieval. Our experiments show that many of these techniques can increase retrieval performance. We also address the problem of automatic creation of parallel corpora which are essential for cross-lingual information retrieval and other natural language processing tasks, including machine translation. We describe algorithms that we have developed to automatically identify parallel documents for Indonesian and English. We also investigate the applicability of our identification algorithms for other languages that use the Latin alphabet including German and French. 292 pp. Englisch. Bookseller Inventory # 9783639021646

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Jelita Asian
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Book Description VDM Verlag Jun 2009, 2009. Taschenbuch. Book Condition: Neu. Neuware - In this thesis, we investigate information retrieval techniques for Indonesian. Stemming is the process of reducing morphological variants of a word to a common stem form. Although several stemming algorithms have been proposed for Indonesian, there is no consensus on which gives better performance. We empirically explore these stemming algorithms, propose novel extensions to the best algorithm, develop a new Indonesian stemmer, and show that these can improve stemming correctness. We propose a range of techniques to enhance the performance of Indonesian information retrieval. Our experiments show that many of these techniques can increase retrieval performance. We also address the problem of automatic creation of parallel corpora which are essential for cross-lingual information retrieval and other natural language processing tasks, including machine translation. We describe algorithms that we have developed to automatically identify parallel documents for Indonesian and English. We also investigate the applicability of our identification algorithms for other languages that use the Latin alphabet including German and French. 292 pp. Englisch. Bookseller Inventory # 9783639021646

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Book Description VDM Verlag Jun 2009, 2009. Taschenbuch. Book Condition: Neu. This item is printed on demand - Print on Demand Neuware - In this thesis, we investigate information retrieval 292 pp. Englisch. Bookseller Inventory # 9783639021646

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Book Description VDM Verlag, 2009. Paperback. Book Condition: New. Language: English . Brand New Book. In this thesis, we investigate information retrieval techniques for Indonesian. Stemming is the process of reducing morphological variants of a word to a common stem form. Although several stemming algorithms have been proposed for Indonesian, there is no consensus on which gives better performance. We empirically explore these stemming algorithms, propose novel extensions to the best algorithm, develop a new Indonesian stemmer, and show that these can improve stemming correctness. We propose a range of techniques to enhance the performance of Indonesian information retrieval. Our experiments show that many of these techniques can increase retrieval performance. We also address the problem of automatic creation of parallel corpora which are essential for cross-lingual information retrieval and other natural language processing tasks, including machine translation. We describe algorithms that we have developed to automatically identify parallel documents for Indonesian and English. We also investigate the applicability of our identification algorithms for other languages that use the Latin alphabet including German and French. Bookseller Inventory # KNV9783639021646

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