th CICLing 2009 markedthe 10 anniversary of the Annual Conference on Intel- gent Text Processing and Computational Linguistics. The CICLing conferences provide a wide-scope forum for the discussion of the art and craft of natural language processing research as well as the best practices in its applications. This volume contains ?ve invited papers and the regular papers accepted for oral presentation at the conference. The papers accepted for poster presentation were published in a special issue of another journal (see the website for more information). Since 2001, the proceedings of CICLing conferences have been published in Springer’s Lecture Notes in Computer Science series, as volumes 2004, 2276, 2588, 2945, 3406, 3878, 4394, and 4919. This volume has been structured into 12 sections: – Trends and Opportunities – Linguistic Knowledge Representation Formalisms – Corpus Analysis and Lexical Resources – Extraction of Lexical Knowledge – Morphology and Parsing – Semantics – Word Sense Disambiguation – Machine Translation and Multilinguism – Information Extraction and Text Mining – Information Retrieval and Text Comparison – Text Summarization – Applications to the Humanities A total of 167 papers by 392 authors from 40 countries were submitted for evaluation by the International Program Committee, see Tables 1 and 2. This volume contains revised versions of 44 papers, by 120 authors, selected for oral presentation; the acceptance rate was 26. 3%.

CICLing 2004 was the 5th Annual Conference on Intelligent Text Processing and Computational Linguistics; see www.CICLing.org. CICLing conferences are intended to provide a balanced view of the cutting-edge developments in both theoretical foundations of computational linguistics and the practice of natural language text processing with its numerous applications. A feature of CICLing conferences is their wide scope that covers nearly all areas of computational linguistics and all aspects of natural language processing applications. These conferences are a forum for dialogue between the specialists working in the two areas. This year we were honored by the presence of our invited speakers Martin KayofStanfordUniversity,PhilipResnikoftheUniversityofMaryland,Ricardo Baeza-Yates of the University of Chile, and Nick Campbell of the ATR Spoken Language Translation Research Laboratories. They delivered excellent extended lectures and organized vivid discussions. Of129submissionsreceived(74fullpapersand44shortpapers),aftercareful international reviewing 74 papers were selected for presentation (40 full papers and35shortpapers),writtenby176authorsfrom21countries:Korea(37),Spain (34), Japan (22), Mexico (15), China (11), Germany (10), Ireland (10), UK (10), Singapore (6), Canada (3), Czech Rep. (3), France (3), Brazil (2), Sweden (2), Taiwan (2), Turkey (2), USA (2), Chile (1), Romania (1), Thailand (1), and The Netherlands (1); the ?gures in parentheses stand for the number of authors from the corresponding country.

This book encompasses a collection of topics covering recent advances that are important to the Arabic language in areas of natural language processing, speech and image analysis. This book presents state-of-the-art reviews and fundamentals as well as applications and recent innovations.The book chapters by top researchers present basic concepts and challenges for the Arabic language in linguistic processing, handwritten recognition, document analysis, text classification and speech processing. In addition, it reports on selected applications in sentiment analysis, annotation, text summarization, speech and font analysis, word recognition and spotting and question answering.Moreover, it highlights and introduces some novel applications in vital areas for the Arabic language. The book is therefore a useful resource for young researchers who are interested in the Arabic language and are still developing their fundamentals and skills in this area. It is also interesting for scientists who wish to keep track of the most recent research directions and advances in this area.

Natural language processing (NLP) is a scientific discipline which is found at the interface of computer science, artificial intelligence and cognitive psychology. Providing an overview of international work in this interdisciplinary field, this book gives the reader a panoramic view of both early and current research in NLP. Carefully chosen multilingual examples present the state of the art of a mature field which is in a constant state of evolution. In four chapters, this book presents the fundamental concepts of phonetics and phonology and the two most important applications in the field of speech processing: recognition and synthesis. Also presented are the fundamental concepts of corpus linguistics and the basic concepts of morphology and its NLP applications such as stemming and part of speech tagging. The fundamental notions and the most important syntactic theories are presented, as well as the different approaches to syntactic parsing with reference to cognitive models, algorithms and computer applications.

This book constitutes the refereed proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2009, held in Mexico City, Mexico in March 2009. The 44 revised full papers presented together with 4 invited papers were carefully reviewed and selected from numerous submissions. The papers cover all current issues in computational linguistics research and present intelligent text processing applications.

As technology weaves itself more tightly into everyday life, socio-economic development has become intricately tied to these ever-evolving innovations. Technology management is now an integral element of sound business practices, and this revolution has opened up many opportunities for global communication. However, such swift change warrants greater research that can foresee and possibly prevent future complications within and between organizations. The Handbook of Research on Engineering Innovations and Technology Management in Organizations is a collection of innovative research that explores global concerns in the applications of technology to business and the explosive growth that resulted. Highlighting a wide range of topics such as cyber security, legal practice, and artificial intelligence, this book is ideally designed for engineers, manufacturers, technology managers, technology developers, IT specialists, productivity consultants, executives, lawyers, programmers, managers, policymakers, academicians, researchers, and students.

The ever-growing popularity of Google over the recent decade has required a specific method of man-machine communication: human query should be short, whereas the machine answer may take a form of a wide range of documents. This type of communication has triggered a rapid development in the domain of Information Extraction, aimed at providing the asker with a more precise information. The recent success of intelligent personal assistants supporting users in searching or even extracting information and answers from large collections of electronic documents signals the onset of a new era in man-machine communication – we shall soon explain to our small devices what we need to know and expect valuable answers quickly and automatically delivered. The progress of man-machine communication is accompanied by growth in the significance of applied Computational Linguistics – we need machines to understand much more from the language we speak naturally than it is the case of up-to-date search systems. Moreover, we need machine support in crossing language barriers that is necessary more and more often when facing the global character of the Web. This books reports on the latest developments in the field. It contains 15 chapters written by researchers who aim at making linguistic theories work – for the better understanding between the man and the machine.

This book constitutes the refereed proceedings of the 6th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2005, held in Mexico City, Mexico in February 2005. The 53 revised full papers and 35 revised short papers presented together with 4 invited papers were carefully reviewed and selected from 151 submissions. The papers are organized in topical sections on computational linguistics forum; semantics and discourse; parsing and syntactic disambiguation; morphology; anaphora and conference; word sense disambiguation; lexical resources; natural language generation; machine translation; speech and natural language interfaces; language documentation; information extraction, information retrieval; question answering; summarization; text classification, categorization, and clustering; named entity recognition; language identification; and spelling and style checking.

Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!