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1

Leacock, Claudia. Automated grammatical error detection for language learners. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2010.

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2

International Workshop on Natural Language Generation (6th 1992 Trento, Italy). Aspects of automated natural language generation: 6th international workshop, Trento, Italy, April 5-7, 1992 : proceedings. Berlin: Springer-Verlag, 1992.

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3

International Workshop on Natural Language Generation (6th 1992 Trento, Italy). Aspects of automated natural language generation: 6th International Workshop on Natural Language Generation, Trento, Italy, April 5-7, 1992 : proceedings. Berlin: Springer-Verlag, 1992.

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4

Wu, Chou, and Juang B. H, eds. Pattern recognition in speech and language processing. Boca Raton: CRC Press, 2003.

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5

Vernon, Elizabeth. Decision-making for automation: Hebrew and Arabic script materials in the automated library. [Champaign]: Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign, 1996.

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6

Vernon, Elizabeth. Decision-making for automation: Hebrew and Arabic script materials in the automated library. [Champaign]: Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign, 1996.

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7

W, McManus J., Bynum W. L, and Langley Research Center, eds. Automated concurrent blackboard system generation in C++. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1999.

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8

Agenbroad, James Edward. Nonromanization: Prospects for improving automated cataloging of items in other writing systems. Washington: Cataloging Forum, Library of Congress, 1992.

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9

IFLA, Satellite Meeting (2nd 1993 Madrid Spain). Automated systems for access to multilingual and multiscript library materials: Proceedings of the Second IFLA Satellite Meeting, Madrid, August 18-19, 1993. München: K.G. Saur, 1994.

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10

Wooldridge, Michael, Sarit Kraus, and Shaheen Fatima. Principles of Automated Negotiation. Cambridge University Press, 2015.

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11

Wooldridge, Michael, Sarit Kraus, and Shaheen Fatima. Principles of Automated Negotiation. Cambridge University Press, 2014.

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12

Principles of Automated Negotiation. Cambridge University Press, 2014.

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13

Language, Living. LL Triple Play Plus English: Upgrade (Living Language). Living Language, 1997.

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14

Leacock, Claudia, Martin Chodorow, Michael Gamon, and Joel Tetreault. Automated Grammatical Error Detection for Language Learners. Morgan & Claypool Publishers, 2014.

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15

Mehler, Alexander, and Chris Biemann. Text Mining: From Ontology Learning to Automated Text Processing Applications. Springer, 2014.

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16

Mehler, Alexander, and Chris Biemann. Text Mining: From Ontology Learning to Automated Text Processing Applications. Springer, 2016.

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17

Mehler, Alexander, and Chris Biemann. Text Mining: From Ontology Learning to Automated Text Processing Applications. Springer, 2014.

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18

Leacock, Claudia, Martin Chodorow, Michael Gamon, and Joel Tetreault. Automated Grammatical Error Detection for Language Learners: Second Edition. Morgan & Claypool Publishers, 2014.

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19

(Editor), Robert Dale, Eduard Hovy (Editor), Dietmar Rösner (Editor), and Oliviero Stock (Editor), eds. Aspects of Automated Natural Language Generation: 6th International Workshop on Natural Language Generation Trento, Italy, April 5-7, 1992. Proceedings (Lecture Notes in Computer Science). Springer, 1992.

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20

Automated concurrent blackboard system generation in C++. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1999.

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21

Zechner, Klaus, and Keelan Evanini. Automated Speaking Assessment: Using Language Technologies to Score Spontaneous Speech. Taylor & Francis Group, 2019.

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22

Zechner, Klaus, and Keelan Evanini. Automated Speaking Assessment: Using Language Technologies to Score Spontaneous Speech. Taylor & Francis Group, 2019.

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23

Zechner, Klaus, and Keelan Evanini. Automated Speaking Assessment: Using Language Technologies to Score Spontaneous Speech. Taylor & Francis Group, 2019.

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24

Zechner, Klaus, and Keelan Evanini. Automated Speaking Assessment: Using Language Technologies to Score Spontaneous Speech. Taylor & Francis Group, 2019.

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25

Vernon, Elizabeth. Decision Making for Automation: Hebrew and Arabic Script Materials in the Automated Library (Occasional Papers, No 205). Univ of Illinois Graduate School of, 1996.

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26

Personnel Administration in an Automated Environment. Routledge, 2014.

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27

Etude de la traduction automatique des bulletins météorologiques. Montréal, Québec, Canada: Thomas Leplus, 2004.

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28

Nonromanization: Prospects for Improving Automated Cataloging of Items in Other Writing Systems (Opinion Papers, No 3). Jim Agenbroad, 1994.

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29

International Federation of Library Associations and Institutions. Section on Preservation and Conservation (Corporate Author), C. Bossmeyer (Editor), Willem R. H. Koops (Editor), and Stephen W. Massil (Editor), eds. Automated Systems for Access to Multi-Lingual and Multiscript Library Materials: Problems and Solution : Paper from the Pre-Conference Held at Nihon (Ifla Publications, 38). K G Saur Verlag Gmbh & Co, 1987.

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30

Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining. Wiley, 2015.

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31

C, Bossmeyer, Massil Stephen W, International Federation of Library Associations and Institutions. Section of Library Services to Multicultural Populations., and International Federation of Library Associations and Institutions. Section on Information Technology., eds. Automated systems for access to multilingual and multiscript library materials: Problems and solutions : papers from the pre-conference held at Nihon Daigaku Kaikan Tokyo, Japan, August 21-22, 1986. München: K.G. Saur, 1987.

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32

Megerdoomian, Karine. Computational Linguistics. Edited by Anousha Sedighi and Pouneh Shabani-Jadidi. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198736745.013.19.

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This chapter introduces the fields of Computational Linguistics (CL)—the computational modelling of linguistic representations and theories—and Natural Language Processing (NLP)—the design and implementation of tools for automated language understanding and production—and discusses some of the existing tensions between the formal approach to linguistics and the current state of the research and development in CL and NLP. The paper goes on to explain the specific challenges faced by CL and NLP for Persian, much of it derived from the intricacies presented by the Perso-Arabic script in automatically identifying word and phrase boundaries in text, as well as difficulties in automatic processing of compound words and light verb constructions. The chapter then provides an overview of the state of the art in current and recent CL and NLP for Persian. It concludes with areas for improvement and suggestions for future directions.
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33

Caselli, Tommaso, Eduard Hovy, Martha Palmer, and Piek Vossen, eds. Computational Analysis of Storylines. Cambridge University Press, 2021. http://dx.doi.org/10.1017/9781108854221.

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Event structures are central in Linguistics and Artificial Intelligence research: people can easily refer to changes in the world, identify their participants, distinguish relevant information, and have expectations of what can happen next. Part of this process is based on mechanisms similar to narratives, which are at the heart of information sharing. But it remains difficult to automatically detect events or automatically construct stories from such event representations. This book explores how to handle today's massive news streams and provides multidimensional, multimodal, and distributed approaches, like automated deep learning, to capture events and narrative structures involved in a 'story'. This overview of the current state-of-the-art on event extraction, temporal and casual relations, and storyline extraction aims to establish a new multidisciplinary research community with a common terminology and research agenda. Graduate students and researchers in natural language processing, computational linguistics, and media studies will benefit from this book.
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