This book investigates two major systems: firstly, co-operating distributed grammar systems, where the grammars work on one common sequential form and the co-operation is realized by the control of the sequence of active grammars; secondly, parallel communicating grammar systems, where each grammar works on its own sequential form and co-operation is done by means of communicating between grammars. The investigation concerns hierarchies with respect to different variants of co-operation, relations with classical formal language theory, syntactic parameters such as the number of components and their size, power of synchronization, and general notions generated from artificial intelligence.

Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design models and systems for a wide range of applications.

In the global research community, English has become the main language of scholarly publishing in many disciplines. At the same time, online machine translation systems have become increasingly easy to access and use. Is this a researcher's match made in heaven, or the road to publication perdition? Here Lynne Bowker and Jairo Buitrago Ciro introduce the concept of machine translation literacy, a new kind of literacy for scholars and librarians in the digital age. For scholars, they explain how machine translation works, how it is (or could be) used for scholarly communication, and how both native and non-native English-speakers can write in a translation-friendly way in order to harness its potential. Native English speakers can continue to write in English, but expand the global reach of their research by making it easier for their peers around the world to access and understand their works, while non-native English speakers can write in their mother tongues, but leverage machine translation technology to help them produce draft publications in English. For academic librarians, the authors provide a framework for supporting researchers in all disciplines as they grapple with producing translation-friendly texts and using machine translation for scholarly communication-a form of support that will only become more important as campuses become increasingly international and as universities continue to strive to excel on the global stage. Machine Translation and Global Research is a must-read for scientists, researchers, students, and librarians eager to maximize the global reach and impact of any form of scholarly work.

Accompanying continued industrial production and sales of artificial intelligence and expert systems is the risk that difficult and resistant theoretical problems and issues will be ignored. The participants at the Third Tinlap Workshop, whose contributions are contained in Theoretical Issues in Natural Language Processing, remove that risk. They discuss and promote theoretical research on natural language processing, examinations of solutions to current problems, development of new theories, and representations of published literature on the subject. Discussions among these theoreticians in artificial intelligence, logic, psychology, philosophy, and linguistics draw a comprehensive, up-to-date picture of the natural language processing field.

Natural language generation (NLG) is the process wherein computers produce output in readable human languages. Such output takes many forms, including news articles, sports reports, prose fiction, and poetry. These computer-generated texts are often indistinguishable from human-written texts, and they are increasingly prevalent. NLG is here, and it is everywhere. However, readers are often unaware that what they are reading has been computer-generated. This Element considers how NLG conforms to and confronts traditional understandings of authorship and what it means to be a reader. It argues that conventional conceptions of authorship, as well as of reader responsibility, change in instances of NLG. What is the social value of a computer-generated text? What does NLG mean for modern writing, publishing, and reading practices? Can an NLG system be considered an author? This Element explores such question, while presenting a theoretical basis for future studies.

Voice assistants, automated customer service agents, and other cutting-edge human-to-computer interactions rely on accurately interpreting language as it is written and spoken. Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you'll explore the core tools and techniques required to build a huge range of powerful NLP apps. about the technologyNatural language processing is the part of AI dedicated to understanding and generating human text and speech. NLP covers a wide range of algorithms and tasks, from classic functions such as spell checkers, machine translation, and search engines to emerging innovations like chatbots, voice assistants, and automatic text summarization. Wherever there is text, NLP can be useful for extracting meaning and bridging the gap between humans and machines. about the book Real-world Natural Language Processing teaches you how to create practical NLP applications using Python and open source NLP libraries such as AllenNLP and Fairseq. In this practical guide, you'll begin by creating a complete sentiment analyzer, then dive deep into each component to unlock the building blocks you'll use in all different kinds of NLP programs. By the time you're done, you'll have the skills to create named entity taggers, machine translation systems, spelling correctors, and language generation systems. what's inside Design, develop, and deploy basic NLP applications NLP libraries such as AllenNLP and Fairseq Advanced NLP concepts such as attention and transfer learning about the readerAimed at intermediate Python programmers. No mathematical or machine learning knowledge required. about the author Masato Hagiwara received his computer science PhD from Nagoya University in 2009, focusing on Natural Language Processing and machine learning. He has interned at Google and Microsoft Research, and worked at Baidu Japan, Duolingo, and Rakuten Institute of Technology. He now runs his own consultancy business advising clients, including startups and research institutions.

This book constitutes the proceedings of the 23rd International Conference on Developments in Language Theory, DLT 2019, held in Warsaw, Poland, in August 2019. The 20 full papers presented together with three invited talks were carefully reviewed and selected from 30 submissions. The papers cover the following topics and areas: combinatorial and algebraic properties of words and languages; grammars, acceptors and transducers for strings, trees, graphics, arrays; algebraic theories for automata and languages; codes; efficient text algorithms; symbolic dynamics; decision problems; relationships to complexity theory and logic; picture description and analysis, polyominoes and bidimensional patterns; cryptography; concurrency; celluar automata; bio-inspired computing; quantum computing.

This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshop on Graphics Recognition, GREC 2017, held in Kyoto, Japan, in November 2017. The 10 revised full papers presented were carefully reviewed and selected from 14 initial submissions. They contain both classical and emerging topics of graphics rcognition, namely analysis and detection of diagrams, search and classification, optical music recognition, interpretation of engineering drawings and maps.

This book constitutes the thoroughly refereed proceedings of the 8th Joint International Semantic Technology Conference, JIST 2018, held in Awaji, Japan, in November 2018. The 23 full papers and 6 short papers presented were carefully reviewed and selected from 75 submissions. They present applications of semantic technologies, theoretical results, new algorithms and tools to facilitate the adoption of semantic technologies and are organized in topical sections on knowledge graphs; data management; question answering and NLP; ontology and reasoning; government open data; and semantic web for life sciences.

This book constitutes the thoroughly refereed post conference proceedings of the 4th edition of the Semantic Web Evaluation Challenge, SemWebEval 2018, co-located with the 15th European Semantic Web conference, held in Heraklion, Greece, in June 2018. This book includes the descriptions of all methods and tools that competed at SemWebEval 2018, together with a detailed description of the tasks, evaluation procedures and datasets. The 18 revised full papers presented in this volume were carefully reviewed and selected from 24 submissions. The contributions are grouped in the areas: the mighty storage challenge; open knowledge extraction challenge; question answering over linked data challenge; semantic sentiment analysis.

This book constitutes the proceedings of the 17th China National Conference on Computational Linguistics, CCL 2018, and the 6th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2018, held in Changsha, China, in October 2018. The 33 full papers presented in this volume were carefully reviewed and selected from 84 submissions. They are organized in topical sections named: Semantics; machine translation; knowledge graph and information extraction; linguistic resource annotation and evaluation; information retrieval and question answering; text classification and summarization; social computing and sentiment analysis; and NLP applications.

The two-volume set LNCS 10761 + 10762 constitutes revised selected papers from the CICLing 2017 conference which took place in Budapest, Hungary, in April 2017. The total of 90 papers presented in the two volumes was carefully reviewed and selected from numerous submissions. In addition, the proceedings contain 4 invited papers. The papers are organized in the following topical sections: Part I: general; morphology and text segmentation; syntax and parsing; word sense disambiguation; reference and coreference resolution; named entity recognition; semantics and text similarity; information extraction; speech recognition; applications to linguistics and the humanities. Part II: sentiment analysis; opinion mining; author profiling and authorship attribution; social network analysis; machine translation; text summarization; information retrieval and text classification; practical applications.

This book presents techniques for audio search, aimed to retrieve information from massive speech databases by using audio query words. The authors examine different features, techniques and evaluation measures attempted by researchers around the world. The topics covered also include available databases, software / tools, patents / copyrights, and different platforms for benchmarking. The content is relevant for developers, academics, and students.

This book constitutes the proceedings of the 22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018, held in Porto, Portugal, in September 2018. The 51 full papers, 17 short papers, and 13 poster and tutorial papers presented in this volume were carefully reviewed and selected from 81 submissions. The general theme of TPDL 2018 was Digital Libraries for Open Knowledge. The papers present a wide range of the following topics: Metadata, Entity Disambiguation, Data Management, Scholarly Communication, Digital Humanities, User Interaction, Resources, Information Extraction, Information Retrieval, Recommendation.

This book constitutes the refereed proceedings of the 13th International Conference on Computational Processing of the Portuguese Language, PROPOR 2018, held in Canela, RS, Brazil, in September 2018. The 42 full papers, 3 short papers and 4 other papers presented in this volume were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections named: Corpus Linguistics, Information Extraction, LanguageApplications, Language Resources, Sentiment Analysis and Opinion Mining, Speech Processing, and Syntax and Parsing.

This book constitutes the proceedings of the 22nd International Conference on Developments in Language Theory, DLT 2018, held in Tokyo, Japan, in September 2018. The 39 full papers presented in this volume were carefully reviewed and selected from 84 submissions. The papers cover the following topics and areas: combinatorial and algebraic properties of words and languages; grammars, acceptors and transducers for strings, trees, graphics, arrays; algebraic theories for automata and languages; codes; efficient text algorithms; symbolic dynamics; decision problems; relationships to complexity theory and logic; picture description and analysis, polyominoes and bidimensional patterns; cryptography; concurrency; celluar automata; bio-inspired computing; quantum computing.

This book constitutes the thoroughly refereed proceedings of the Third International Conference on Big Data, Cloud and Applications, BDCA 2018, held in Kenitra, Morocco, in April 2018.The 45 revised full papers presented in this book were carefully selected from 99 submissions with a thorough double-blind review process. They focus on the following topics: big data, cloud computing, machine learning, deep learning, data analysis, neural networks, information system and social media, image processing and applications, and natural language processing.

This book constitutes the thoroughly refereed proceedings of the 31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, held in Montreal, QC, Canada, in June 2018. The 53 full papers and 33 short papers presented were carefully reviewed and selected from 146 submissions. They are organized in the following topical sections: constraint solving and optimization; data mining and knowledge discovery; evolutionary computation; expert systems and robotics; knowledge representation, machine learning; meta-heuristics; multi-agent systems; natural language processing; neural networks; planning, scheduling and spatial reasoning; rough sets, Internet of Things (IoT), ubiquitous computing and big data; data science, privacy, and security; inelligent systems approaches in information extraction; and artificial intelligence, law and justice.

This book constitutes the refereed proceedings of the 24th International Conference on Applications of Natural Language to Information Systems, NLDB 2019, held in Salford, UK, in June 2019. The 21 full papers and 16 short papers were carefully reviewed and selected from 75 submissions. The papers are organized in the following topical sections: argumentation mining and applications; deep learning, neural languages and NLP; social media and web analytics; question answering; corpus analysis; semantic web, open linked data, and ontologies; natural language in conceptual modeling; natural language and ubiquitous computing; and big data and business intelligence.

This book constitutes the refereed proceedings of the 12th International Conference, NooJ 2018, held in Palermo, Italy, in June 2018.The 17 revised full papers and 3 short papers presented in this volume were carefully reviewed and selected from 48 submissions. NooJ is a linguistic development environment that provides tools for linguists to construct linguistic resources that formalize a large gamut of linguistic phenomena: typography, orthography, lexicons for simple words, multiword units and discontinuous expressions, inflectional and derivational morphology, local, structural and transformational syntax, and semantics. The papers in this volume are organized in topical sections on vocabulary and morphology; syntax and semantics; and natural language processing applications.

This book provides an overview of a recent and flexible approach to speech synthesis design to develop the first statistical parametric speech synthesizer for Ibibio, a West African tonal language. The design precludes the inflexibility encountered when modeling tonal features of the language and can be used for other tonal African languages. Mobile use and technological innovations in developing African nations have exploded. With mobile technology, many of the barriers caused by infrastructure issues have vanished. In order to address issues that are unique to African tonal languages, the book uses Ibibio as a model. The text reviews the language's speech characteristics, required for building the front end components of the design and propose a finite state transducer (FST), useful for modelling the language's tonetactics. The statistical parametric approach discussed in the text, implements the Hidden Markov Model (HMM) technique, with the goal of creating a generic structure that learns the model from the text itself, and uses the data-driven approach to input specification.