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Ontology Learning From Text
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Book Synopsis Ontology Learning and Population from Text by : Philipp Cimiano
Download or read book Ontology Learning and Population from Text written by Philipp Cimiano and published by Springer Science & Business Media. This book was released on 2006-12-11 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade, ontologies have received much attention within computer science and related disciplines, most often as the semantic web. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications discusses ontologies for the semantic web, as well as knowledge management, information retrieval, text clustering and classification, as well as natural language processing. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is structured for research scientists and practitioners in industry. This book is also suitable for graduate-level students in computer science.
Book Synopsis Ontology Learning from Text by : Paul Buitelaar
Download or read book Ontology Learning from Text written by Paul Buitelaar and published by IOS Press. This book was released on 2005 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: The latest title in Black Library's premium line. Perturabo - master of siegecraft, and executioner of Olympia. Long has he lived in the shadow of his more favoured primarch brothers, frustrated by the mundane and ignominious duties which regularly fall to his Legion. When Fulgrim offers him the chance to lead an expedition in search of an ancient and destructive xenos weapon, the Iron Warriors and the Emperor's Children unite and venture deep into the heart of the great warp-rift known only as 'the Eye'. Pursued by a ragged band of survivors from Isstvan V and the revenants of a dead eldar world, they must work quickly if they are to unleash the devastating power of the Angel Exterminatus
Book Synopsis Ontology Learning and Population: Bridging the Gap Between Text and Knowledge by : P. Buitelaar
Download or read book Ontology Learning and Population: Bridging the Gap Between Text and Knowledge written by P. Buitelaar and published by IOS Press. This book was released on 2008-01-31 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: The promise of the Semantic Web is that future web pages will be annotated not only with bright colors and fancy fonts as they are now, but with annotation extracted from large domain ontologies that specify, to a computer in a way that it can exploit, what information is contained on the given web page. The presence of this information will allow software agents to examine pages and to make decisions about content as humans are able to do now. The classic method of building an ontology is to gather a committee of experts in the domain to be modeled by the ontology, and to have this committee agree on which concepts cover the domain, on which terms describe which concepts, on what relations exist between each concept and what the possible attributes of each concept are. All ontology learning systems begin with an ontology structure, which may just be an empty logical structure, and a collection of texts in the domain to be modeled. An ontology learning system can be seen as an interplay between three things: an existing ontology, a collection of texts, and lexical syntactic patterns. The Semantic Web will only be a reality if we can create structured, unambiguous ontologies that model domain knowledge that computers can handle. The creation of vast arrays of such ontologies, to be used to mark-up web pages for the Semantic Web, can only be accomplished by computer tools that can extract and build large parts of these ontologies automatically. This book provides the state-of-art of many automatic extraction and modeling techniques for ontology building. The maturation of these techniques will lead to the creation of the Semantic Web.
Book Synopsis Ontology Learning for the Semantic Web by : Alexander Maedche
Download or read book Ontology Learning for the Semantic Web written by Alexander Maedche and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ontology Learning for the Semantic Web explores techniques for applying knowledge discovery techniques to different web data sources (such as HTML documents, dictionaries, etc.), in order to support the task of engineering and maintaining ontologies. The approach of ontology learning proposed in Ontology Learning for the Semantic Web includes a number of complementary disciplines that feed in different types of unstructured and semi-structured data. This data is necessary in order to support a semi-automatic ontology engineering process. Ontology Learning for the Semantic Web is designed for researchers and developers of semantic web applications. It also serves as an excellent supplemental reference to advanced level courses in ontologies and the semantic web.
Book Synopsis Ontology Learning and Population by : Paul Buitelaar
Download or read book Ontology Learning and Population written by Paul Buitelaar and published by IOS Press. This book was released on 2008 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: The promise of the Semantic Web is that future web pages will be annotated not only with bright colors and fancy fonts as they are now, but with annotation extracted from large domain ontologies that specify, to a computer in a way that it can exploit, what information is contained on the given web page. The presence of this information will allow software agents to examine pages and to make decisions about content as humans are able to do now. The classic method of building an ontology is to gather a committee of experts in the domain to be modeled by the ontology, and to have this committee.
Book Synopsis Perspectives on Ontology Learning by : J. Lehmann
Download or read book Perspectives on Ontology Learning written by J. Lehmann and published by IOS Press. This book was released on 2014-04-03 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning. Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the creation of simple taxonomical structures, as well as on problems specifically related to knowledge modeling and representation using the Web Ontology Language. Perspectives on Ontology Learning is designed for researchers in the field of semantic technologies and developers of knowledge-based applications. It covers various aspects of ontology learning including ontology quality, user interaction, scalability, knowledge acquisition from heterogeneous sources, as well as the integration with ontology engineering methodologies.
Book Synopsis Knowledge Seeker - Ontology Modelling for Information Search and Management by : Edward H. Y. Lim
Download or read book Knowledge Seeker - Ontology Modelling for Information Search and Management written by Edward H. Y. Lim and published by Springer Science & Business Media. This book was released on 2011-01-31 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Knowledge Seeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The Knowledge Seeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology.
Book Synopsis Artificial Intelligence for Big Data by : Anand Deshpande
Download or read book Artificial Intelligence for Big Data written by Anand Deshpande and published by Packt Publishing Ltd. This book was released on 2018-05-22 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.
Book Synopsis Ontologies of English by : Christopher J. Hall
Download or read book Ontologies of English written by Christopher J. Hall and published by Cambridge University Press. This book was released on 2020-01-02 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: A critical examination of the ways in which English is conceptualised for learning, teaching, and assessment in a range of domains, from both social and cognitive perspectives. Researchers and postgraduates working on English in L1 and L2 educational contexts will find it valuable for research and collaboration.
Book Synopsis Research and Development in Intelligent Systems XXIV by : Max Bramer
Download or read book Research and Development in Intelligent Systems XXIV written by Max Bramer and published by Springer Science & Business Media. This book was released on 2007-12-03 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: An agent in a multi-agent system (MAS) has to generate plans for its individual goal, but these plans may con?ict with those that are already being scheduled or executed by other agents. It must also be able to complete its planning and resolution of these con?icts within a reasonable time to have an acceptable quality plan. Although we adopt hierarchical planning (HP, for example, see [7, 12]) using the decision-theoretic planning (DTP) approach [6] for ef?cient planning, it is not trivial to apply HPO to MAS. In HP, appropriate (abstract) plans are selected level by level to maximize the utility U (p), where where p is the expected ?nal plan comprising a sequence of primitive actions. However, in the MAS context, con?icts between agents affect the ef?ciency and quality of resulting plans. When a con?ict is found at lower levels, an additional sophisticated process for avoiding it (con?ict resolution) must be invoked and some extra actions (such as waiting for synchronization and detouring) may have to be added to the plan. The con?ict resolution process may become costly or fail. Even a single con?ict, if it is dif?cult to resolve, will result in a plan with considerably lower quality than it otherwise would have. As a result, in multi-agent systems, the second- or third-best plans may result in better overall performance.
Book Synopsis An Introduction to Ontology Engineering by : C. Maria Keet
Download or read book An Introduction to Ontology Engineering written by C. Maria Keet and published by . This book was released on 2018-11-07 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Ontology Engineering introduces the student to a comprehensive overview of ontology engineering, and offers hands-on experience that illustrate the theory. The topics covered include: logic foundations for ontologies with languages and automated reasoning, developing good ontologies with methods and methodologies, the top-down approach with foundational ontologies, and the bottomup approach to extract content from legacy material, and a selection of advanced topics that includes Ontology-Based Data Access, the interaction between ontologies and natural languages, and advanced modelling with fuzzy and temporal ontologies. Each chapter contains review questions and exercises, and descriptions of two group assignments are provided as well. The textbook is aimed at advanced undergraduate/postgraduate level in computer science and could fi t a semester course in ontology engineering or a 2-week intensive course. Domain experts and philosophers may fi nd a subset of the chapters of interest, or work through the chapters in a different order. Maria Keet is an Associate Professor with the Department of Computer Science, University of Cape Town, South Africa. She received her PhD in Computer Science in 2008 at the KRDB Research Centre, Free University of Bozen-Bolzano, Italy. Her research focus is on knowledge engineering with ontologies and Ontology, and their interaction with natural language and conceptual data modelling, which has resulted in over 100 peer-reviewed publications. She has developed and taught multiple courses on ontology engineering and related courses at various universities since 2009.
Book Synopsis Semantic Similarity from Natural Language and Ontology Analysis by : Sébastien Harispe
Download or read book Semantic Similarity from Natural Language and Ontology Analysis written by Sébastien Harispe and published by Springer Nature. This book was released on 2022-05-31 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpora analysis and is based on Natural Language Processing techniques and semantic models while the second is based on more or less formal, computer-readable and workable forms of knowledge such as semantic networks, thesauri or ontologies. Semantic measures are widely used today to compare units of language, concepts, instances or even resources indexed by them (e.g., documents, genes). They are central elements of a large variety of Natural Language Processing applications and knowledge-based treatments, and have therefore naturally been subject to intensive and interdisciplinary research efforts during last decades. Beyond a simple inventory and categorization of existing measures, the aim of this monograph is to convey novices as well as researchers of these domains toward a better understanding of semantic similarity estimation and more generally semantic measures. To this end, we propose an in-depth characterization of existing proposals by discussing their features, the assumptions on which they are based and empirical results regarding their performance in particular applications. By answering these questions and by providing a detailed discussion on the foundations of semantic measures, our aim is to give the reader key knowledge required to: (i) select the more relevant methods according to a particular usage context, (ii) understand the challenges offered to this field of study, (iii) distinguish room of improvements for state-of-the-art approaches and (iv) stimulate creativity toward the development of new approaches. In this aim, several definitions, theoretical and practical details, as well as concrete applications are presented.
Book Synopsis Ontology Learning and Population by : P. Buitelaar
Download or read book Ontology Learning and Population written by P. Buitelaar and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The promise of the Semantic Web is that future web pages will be annotated not only with bright colors and fancy fonts as they are now, but with annotation extracted from large domain ontologies that specify, to a computer in a way that it can exploit, what information is contained on the given web page. The presence of this information will allow software agents to examine pages and to make decisions about content as humans are able to do now. The classic method of building an ontology is to gather a committee of experts in the domain to be modeled by the ontology, and to have this committee.
Book Synopsis Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications by : Oscar Castillo
Download or read book Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications written by Oscar Castillo and published by Springer Nature. This book was released on 2020-02-27 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization. The topic is highly relevant as most current intelligent systems and devices use some form of intelligent feature to enhance their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which are of great interest to researchers in these areas. Further, it proposes novel, nature-inspired optimization algorithms and innovative neural models. Featuring contributions on theoretical aspects as well as applications, the book appeals to a wide audience.
Book Synopsis Uncertainty Reasoning for the Semantic Web I by : Paulo C. G. Costa
Download or read book Uncertainty Reasoning for the Semantic Web I written by Paulo C. G. Costa and published by Springer Science & Business Media. This book was released on 2008-12-02 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed first three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2005, 2006, and 2007. The 22 papers presented are revised and strongly extended versions of selected workshops papers as well as invited contributions from leading experts in the field and closely related areas. The present volume represents the first comprehensive compilation of state-of-the-art research approaches to uncertainty reasoning in the context of the semantic Web, capturing different models of uncertainty and approaches to deductive as well as inductive reasoning with uncertain formal knowledge.
Book Synopsis Innovations, Developments, and Applications of Semantic Web and Information Systems by : Lytras, Miltiadis D.
Download or read book Innovations, Developments, and Applications of Semantic Web and Information Systems written by Lytras, Miltiadis D. and published by IGI Global. This book was released on 2018-01-19 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years, there has been an increased advancement and evolution in semantic web and information systems in a variety of fields. The integration of these approaches to ontology engineering, sophisticated methods and algorithms for open linked data extraction, and advanced decision-making creates new opportunities for a bright future. Innovations, Developments, and Applications of Semantic Web and Information Systems is a critical scholarly resource that discusses integrated methods of research and analytics in information technology. Featuring coverage on a broad range of topics, such as cognitive computing, artificial intelligence, machine learning, data analysis, and algorithms, this book is geared towards researchers, academicians, and professionals seeking current information on semantic web and information systems.
Book Synopsis From Data and Information Analysis to Knowledge Engineering by : Myra Spiliopoulou
Download or read book From Data and Information Analysis to Knowledge Engineering written by Myra Spiliopoulou and published by Springer Science & Business Media. This book was released on 2006-04-20 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume collects revised versions of papers presented at the 29th Annual Conference of the Gesellschaft für Klassifikation, the German Classification Society, held at the Otto-von-Guericke-University of Magdeburg, Germany, in March 2005. In addition to traditional subjects like Classification, Clustering, and Data Analysis, converage extends to a wide range of topics relating to Computer Science: Text Mining, Web Mining, Fuzzy Data Analysis, IT Security, Adaptivity and Personalization, and Visualization.
