Page 4
Page 4
Computational linguistics and intelligent text processing ; Vol. 3406 ; 6th International Conference, CICLing 2005, Mexico City, Mexico, February 13-19, 2005, Proceedings
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. An approach that involves natural language analysis techniques for the treatment of software system functional requirements is described in this book. This approach is used as the basis for a process developed to generate sequence diagrams automatically from the textual specification of use cases. This facility has been integrated in the Requirements Engineering Phase of OO-Method, an automatic production environment of software. For this purpose, a translator that is based on natural language parser is used. The translator provides grammatical information to each use case sentence and it identifies the corresponding interaction. The automatic transformation is conceived and specified following an orientation that is based on models and patterns. The results of the validation of the transformation patterns are presented.
Computational Forensic ; 2nd International Workshop, IWCF 2008, Washington, DC, USA, August 7-8, 2008. Proceedings
This book constitutes the refereed proceedings of the Second International Workshop, IWCF 2008, held in Washington, DC, USA, August 2008. The papers are organized in topical sections on trends and challenges; scanner, printer, and prints; human identification; shoeprints; linguistics;decision making and search; speech analysis; signatures and handwriting.
Computational Collective Intelligence ; 12th International Conference, ICCCI 2020, Da Nang, Vietnam, November 30 – December 3, 2020, Proceedings
This volume constitutes the refereed proceedings of the 12th International Conference on Computational Collective Intelligence, ICCCI 2020, held in Da Nang, Vietnam, in November 2020.* The 70 full papers presented were carefully reviewed and selected from 314 submissions. The papers are grouped in topical sections on: knowledge engineering and semantic web; social networks and recommender systems; collective decision-making; applications of collective intelligence; data mining methods and applications; machine learning methods; deep learning and applications for industry 4.0; computer vision techniques; biosensors and biometric techniques; innovations in intelligent systems; natural language processing; low resource languages processing; computational collective intelligence and natural language processing; computational intelligence for multimedia understanding; and intelligent processing of multimedia in web systems.
Computational Cognitive Modeling and Linguistic Theory
This book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science.
Combinatorial pattern matching ; Vol. 3537 ; 16th Annual Symposium, CPM 2005, Jeju Island, Korea, June 19-22, 2005, Proceedings
This volume presents the proceedings of The 16th Annual Symposium on Combinatorial Pattern Matching was heldon Jeju Island, Korea on June 19–22, 2005. the Program Committee accepted 37 of the submissionsto be presented at the conference. This collection of papers offers original research contributionsin combinatorial pattern matching and its applications.In addition to the selected papers
Combinatorial pattern matching ; 19th Annual Symposium, CPM 2008, Pisa, Italy, June 18-20, 2008 Proceedings
This book constitutes the refereed proceedings of the 19th Annual Symposium on Combinatorial Pattern Matching, CPM 2008, held in Pisa, Italy, in June 2008.
Collaboration Technologies and Social Computing ; 26th International Conference, CollabTech 2020, Tartu, Estonia, September 8–11, 2020, Proceedings
This book constitutes the proceedings of the 26th International Conference on Collaboration Technologies and Social Computing, CollabTech 2020. The conference was scheduled to take place in Tartu, Estonia, in September 2020. It was held virtually due to the COVID-19 pandemic. The 10 full and 5 work-in-progress papers presented in this volume were carefully reviewed and selected from 25 submissions.
Cohesion, coherence and temporal reference from an experimental corpus pragmatics perspective
Provides new methodological and theoretical insights into temporal reference and its linguistic expression, from a cross-linguistic experimental corpus pragmatics approach. Verbal tenses, in general, and more specifically the categories of tense, grammatical and lexical aspect are treated as cohesion ties contributing to the temporal coherence of a discourse, as well as to the cognitive temporal coherence of the mental representations built in the language comprehension process. As such, it investigates the phenomenon of temporal reference at the interface between corpus linguistics, theoretical linguistics and pragmatics, experimental pragmatics, psycholinguistics, natural language processing and machine translation.
Cognitive Systems ; Joint Chinese-German Workshop, Shanghai, China, March 7-11, 2005, Revised Selected Papers
This book organized in topical sections on multimodal human-computer interfaces, neuropsychology and neurocomputing, Chinese-German natural language processing and psycholinguistics, as well as information processing and retrieval from the semantic Web for intelligent applications.
Coded Leadership : Developing Scalable Management in an AI-induced Quantum World
Introduces the necessary background to understand the challenges in today’s organizational leadership and how artificial intelligence enables learning to be viewed from a probabilistic framework. Introduction to Quantum Natural Language Processing. Overview of Leadership and AI. The Age of Quantum Superiority. Challenges to Today’s Leadership. AI-induced Strategic Implementation and Organizational Performance.
Clinical text mining : Secondary use of electronic patient records
Describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters.
Mathematical Linguistics
Mathematical Linguistics introduces the mathematical foundations of linguistics to computer scientists, engineers, and mathematicians interested in natural language processing. The book presents linguistics as a cumulative body of knowledge from the ground up, with no prior knowledge of linguistics being assumed, covering more than the average two-semester introductory course in linguistics.This comprehensive, reader-friendly volume offers readers a high-level orientation, discussing the foundations of the field and presenting both the classical work and the most recent results. It covers an extremely rich array of topics including not only syntax and semantics but also phonology and morphology, probabilistic approaches, complexity, learnability, and the analysis of speech and handwriting.
Markov Models for Pattern Recognition : From Theory to Applications
Describes the underlying theoretical concepts - covering Hidden Markov models and Markov chain models - and presents the techniques and algorithmic solutions essential to creating real world applications. The actual use of Markov models in their three main application areas - namely speech recognition, handwriting recognition, and biological sequence analysis - is presented with examples of successful systems.
Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains .
Machine Learning Refined : Foundations, Algorithms, and Applications
Provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.
Machine learning refined : Foundations, algorithms, and applications
Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization
Machine Learning for Multimodal Interaction ; 5th International Workshop, MLMI 2008, Utrecht, The Netherlands, September 8-10, 2008. Proceedings
The 12 revised full papers and 15 revised poster papers presented together with 5 papers of a special session on user requirements and evaluation of multimodal meeting browsers/assistants were carefully reviewed and selected from 47 submissions. The papers cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction, using several communication modalities. Special focus is given to the analysis of non-verbal communication cues and social signal processing, the analysis of communicative content, audio-visual scene analysis, speech processing, interactive systems and applications.
Machine Learning for Multimodal Interaction ; 4th International Workshop, MLMI 2007, Brno, Czech Republic, June 28-30, 2007, Revised Selected Papers
This book contains a selection of revised papers from the 4th Workshop on Machine Learning for Multimodal Interaction (MLMI 2007), which took place in Brno, Czech Republic, during June 28 30, 2007. As in the previous editions of the MLMI series, the 26 chapters of this book cover a large area of topics, from multimodal processing and human computer interaction to video, audio, speech and language processing. The application of machine learning techniques to problems arising in these felds and the design and analysis of software
Machine learning challenges : Evaluating predictive uncertainty, Visual Object Classification, and Recognizing Textual Entailment, 1st Pascal Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers
Constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. 25 papers address three challenges: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; second, recognizing objects from a number of visual object classes in realistic scenes; third, recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding.
Logical aspects of computational linguistics ; 4th International Conference, LACL 2001, Le Croisic, France, June 27-29, 2001, Proceedings
Structural Equations in Language Learning.- On the Distinction between Model-Theoretic and Generative-Enumerative Syntactic Frameworks.- Contributed Papers.- A Formal Definition of Bottom-Up Embedded Push-Down Automata and Their Tabulation Technique.- An Algebraic Approach to French Sentence Structure.- Deductive Parsing of Visual Languages.- Lambek Grammars Based on Pregroups.- An Algebraic Analysis of Clitic Pronouns in Italian.- Consistent Identification in the Limit of Any of the Classes k-Valued Is NP-hard.- Polarized Non-projective Dependency Grammars.- On Mixing Deduction and Substitution in Lambek Categorial Grammars.- A Framework for the Hyperintensional Semantics of Natural Language with Two Implementations.- A Characterization of Minimalist Languages.- of Speech Tagging from a Logical Point of View.- Transforming Linear Context-Free Rewriting Systems into Minimalist Grammars.- Recognizing Head Movement.- Combinators for Paraconsistent Attitudes.- Combining Syntax and Pragmatic Knowledge for the Understanding of Spontaneous Spoken Sentences.- Atomicity of Some Categorially Polyvalent Modifiers.
