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Language resources and computational models are becoming increasingly important for the study of language variation. A main challenge of this interdisciplinary field is that linguistics researchers may not be familiar with these helpful computational tools and many NLP researchers are often not familiar with language variation phenomena. This essential reference introduces researchers to the necessary computational models for processing similar languages, varieties, and dialects. In this book, leading experts tackle the inherent challenges of the field by balancing a thorough discussion of the theoretical background with a meaningful overview of state-of-the-art language technology. The book can be used in a graduate course, or as a supplementary text for courses on language variation, dialectology, and sociolinguistics or on computational linguistics and NLP. Part 1 covers the linguistic fundamentals of the field such as the question of status and language variation. Part 2 discusses data collection and pre-processing methods. Finally, Part 3 presents NLP applications such as speech processing, machine translation, and language-specific issues in Arabic and Chinese.

Language and languages --- Computational linguistics. --- Sociolinguistics. --- Dialectology. --- Variation. --- Dialects --- Language and society --- Society and language --- Sociology of language --- Language and culture --- Linguistics --- Sociology --- Integrational linguistics (Oxford school) --- Automatic language processing --- Language data processing --- Natural language processing (Linguistics) --- Applied linguistics --- Cross-language information retrieval --- Mathematical linguistics --- Multilingual computing --- Characterology of speech --- Language diversity --- Language subsystems --- Language variation --- Linguistic diversity --- Variation in language --- Social aspects --- Sociological aspects --- Data processing

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The Asia Information Retrieval Societies Conference (AIRS) 2010 was the sixth conference in the AIRS series,aiming to bring together international researchers and developers to exchange new ideas and the latest results in information - trieval. The scope of the conference encompassed the theory and practice of all aspects of information retrieval in text, audio, image, video, and multimedia data. AIRS 2010 continued the conference series that grew from the Information Retrieval with Asian Languages (IRAL) workshop series, started in 1996. It has become a mature venue for information retrieval work, ?nding support from the ACM Special Interest Group on Information Retrieval (SIGIR); the Association for Computational Linguistics and Chinese Language Processing (ACLCLP); ROCLING; and the Information Processing Society of Japan, Special Interest GrouponInformationFundamentals andAccess Technologies(IPSJSIG-IFAT). This year saw a sharp rise in the number of submissions over the previous year. A total of 120 papers were submitted, representing work by academics and practitioners not only from Asia, but also from Australia, Europe, North America, etc. The high quality of the work made it di?cult for the dedicated programcommitteetodecidewhichpaperstofeatureattheconference.Through adouble-blindreviewingprocess,26submissions(21%)wereacceptedasfulloral papers and 31 (25%) were accepted as short posters. The success of this conferencewas only possible with the support of allof the authorswho submitted papers for review, the programcommittee members who constructively assessedthe submissions, and the registered conference delegates. We thank them for their support of this conference, and for their long-term support of this Asian-centric venue for IR research and development.

Information retrieval --- Complex analysis --- Computer science --- Programming --- Computer architecture. Operating systems --- Information systems --- Computer. Automation --- gegevensopslag --- complexe analyse (wiskunde) --- applicatiebeheer --- apps --- informatica --- informatiesystemen --- database management --- programmatielogica --- algoritmen --- architectuur (informatica)

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People make sense of a text by identifying the semantic relations which connect the entities or concepts described by that text. A system which aspires to human-like performance must also be equipped to identify, and learn from, semantic relations in the texts it processes. Understanding even a simple sentence such as "Opportunity and Curiosity find similar rocks on Mars" requires recognizing relations (rocks are located on Mars, signalled by the word on) and drawing on already known relations (Opportunity and Curiosity are instances of the class of Mars rovers). A language-understanding system should be able to find such relations in documents and progressively build a knowledge base or even an ontology. Resources of this kind assist continuous learning and other advanced language-processing tasks such as text summarization, question answering and machine translation. The book discusses the recognition in text of semantic relations which capture interactions between base noun phrases. After a brief historical background, we introduce a range of relation inventories of varying granularity, which have been proposed by computational linguists. There is also variation in the scale at which systems operate, from snippets all the way to the whole Web, and in the techniques of recognizing relations in texts, from full supervision through weak or distant supervision to self-supervised or completely unsupervised methods. A discussion of supervised learning covers available datasets, feature sets which describe relation instances, and successful algorithms. An overview of weakly supervised and unsupervised learning zooms in on the acquisition of relations from large corpora with hardly any annotated data. We show how bootstrapping from seed examples or patterns scales up to very large text collections on the Web. We also present machine learning techniques in which data redundancy and variability lead to fast and reliable relation extraction.

Artificial intelligence. --- Natural language processing (Computer science). --- Computational linguistics. --- Artificial Intelligence. --- Natural Language Processing (NLP). --- Computational Linguistics.

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