03853nam a22004935i 4500001001800000003000900018005001700027007001500044008004100059020001800100020001900118024003500137082001600172100003100188245016900219264004600388300003500434336002600469337002600495338003600521347002400557490005900581505104300640520101801683650001702701650004702718650003702765650002202802650003102824650002302855650001702878650003102895650001202926650004202938650002302980650003903003700003503042700003203077710003403109773002003143776003603163830005903199856010103258978-1-4020-6046-5DE-He21320260521092132.0cr nn 008mamaa100301s2007    ne |    s    |||| 0|eng d  a9781402060465  a997814020604657 a10.1007/978-1-4020-6046-52doi04a410.2852231 aSoudi, Abdelhadi.eeditor.10aArabic Computational Morphologyh[electronic resource] :bKnowledge-based and Empirical Methods /cedited by Abdelhadi Soudi, Antal van den Bosch, Günter Neumann. 1aDordrecht :bSpringer Netherlands,c2007.  aVIII, 308 p.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aText, Speech and Language Technology,x1386-291X ;v380 aArabic Computational Morphology: Knowledge-based and Empirical Methods -- On Arabic Transliteration -- Issues in Arabic Morphological Analysis -- Knowledge-Based Methods -- A Syllable-based Account of Arabic Morphology -- Inheritance-based Approach to Arabic Verbal Root-and-Pattern Morphology -- Arabic Computational Morphology: A Trade-off Between Multiple Operations and Multiple Stems -- Grammar-Lexis Relations in the Computational Morphology of Arabic -- Empirical Methods -- Learning to Identify Semitic Roots -- Automatic Processing of Modern Standard Arabic Text -- Supervised and Unsupervised Learning of Arabic Morphology -- Memory-based Morphological Analysis and Part-of-speech Tagging of Arabic -- Integration of Arabic Morphology in Larger Applications -- Light Stemming for Arabic Information Retrieval -- Adapting Morphology for Arabic Information Retrieval* -- Arabic Morphological Representations for Machine Translation -- Arabic Morphological Generation and its Impact on the Quality of Machine Translation to Arabic.  aThe morphology of Arabic poses special challenges to computational natural language processing systems. The exceptional degree of ambiguity in the writing system, the rich morphology, and the highly complex word formation process of roots and patterns all contribute to making computational approaches to Arabic very challenging. Indeed many computational linguists across the world have taken up this challenge over time, and many of the researchers with a track record in this research area have contributed to this book. The book's subtitle aims to reflect that widely different computational approaches to the Arabic morphological system have been proposed. These accounts fall into two main paradigms: the knowledge-based and the empirical. Since morphological knowledge plays an essential role in any higher-level understanding and processing of Arabic text, the book also features a part on the role of Arabic morphology in larger applications, i.e. Information Retrieval (IR) and Machine Translation (MT). 0aLINGUISTICS. 0aINFORMATION STORAGE AND RETRIEVAL SYSTEMS. 0aTRANSLATORS (COMPUTER PROGRAMS). 0aARABIC LANGUAGES. 0aCOMPUTATIONAL LINGUISTICS. 0aSEMITIC LANGUAGES.14aLINGUISTICS.24aCOMPUTATIONAL LINGUISTICS.24aARABIC.24aLANGUAGE TRANSLATION AND LINGUISTICS.24aSEMITIC LANGUAGES.24aINFORMATION STORAGE AND RETRIEVAL.1 aBosch, Antal van den.eeditor.1 aNeumann, Günter.eeditor.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9781402060458 0aText, Speech and Language Technology,x1386-291X ;v3840uhttp://dx.doi.org/10.1007/978-1-4020-6046-5zVer el texto completo en las instalaciones del CICY