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Standard formalisms for knowledge representation such as RDFS or OWL have been recently developed by the semantic web community and are now in place. However, the crucial question still remains: how will we acquire all the knowledge available in people's heads to feed our machines? Natural language is THE means of communication for humans, and consequently texts are massively available on the Web. Terabytes and terabytes of texts containing opinions, ideas, facts and information of all sorts are waiting to be mined for interesting patterns and relationships, or used to annotate documents to facilitate their retrieval. A semantic web which ignores the massive amount of information encoded in text, might actually be a semantic, but not a very useful, web. Knowledge acquisition, and in particular ontology learning from text, actually has to be regarded as a crucial step within the vision of a semantic web. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications presents approaches for ontology learning from text and will be relevant for researchers working on text mining, natural language processing, information retrieval, semantic web and ontologies. Containing introductory material and a quantity of related work on the one hand, but also detailed descriptions of algorithms, evaluation procedures etc. on the other, this book is suitable for novices, and experts in the field, as well as lecturers. Datasets, algorithms and course material can be downloaded at http://www.cimiano.de/olp. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is designed for practitioners in industry, as well researchers and graduate-level students in computer science.

ontologie --- database management --- Computer. Automation --- robots --- Computer architecture. Operating systems --- Metaphysics --- Information systems --- informatiesystemen --- Artificial intelligence. Robotics. Simulation. Graphics --- computernetwerken --- multimedia --- ontology [metaphysics] --- ICT (informatie- en communicatietechnieken) --- Computational linguistics. --- Information retrieval. --- Knowledge acquisition (Expert systems). --- Natural language processing (Computer science). --- Ontology. --- Semantic Web. --- Information theory. --- Artificial intelligence. --- Database management. --- Multimedia systems. --- Computer Communication Networks. --- Theory of Computation. --- Information Systems Applications (incl. Internet). --- Artificial Intelligence. --- Database Management. --- Multimedia Information Systems. --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Information storage and retrieval systems --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Communication theory --- Communication --- Cybernetics --- Computers. --- Application software. --- Multimedia information systems. --- Computer communication systems. --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Calculators --- Cyberspace --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Distributed processing --- Knowledge acquisition (Expert systems) --- Natural language processing (Computer science)

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To date, the relation between multilingualism and the Semantic Web has not yet received enough attention in the research community. One major challenge for the Semantic Web community is to develop architectures, frameworks and systems that can help in overcoming national and language barriers, facilitating equal access to information produced in different cultures and languages. As such, this volume aims at documenting the state-of-the-art with regard to the vision of a Multilingual Semantic Web, in which semantic information will be accessible in and across multiple languages. The Multilingual Semantic Web as envisioned in this volume will support the following functionalities:  (1) responding to information needs in any language with regard to semantically structured data available on the Semantic Web and Linked Open Data (LOD) cloud, (2) verbalizing and accessing semantically structured data, ontologies or other conceptualizations in multiple languages, (3) harmonizing, integrating, aggregating, comparing and repurposing semantically structured data across languages, and (4) aligning and reconciling ontologies or other conceptualizations across languages. The volume is divided into three main sections: Principles, Methods and Applications. The section on “Principles” discusses models, architectures, and methodologies that enrich the current Semantic Web architecture with features necessary to handle multiple languages. The section on “Methods” describes algorithms and approaches for solving key issues related to the construction of the Multilingual Semantic Web. The section on “Applications” describes the use of Multilingual Semantic Web based approaches in the context of several  application domains. This volume is essential reading for all academic and industrial researchers who want to embark on this new research field at the intersection of various research topics, including the Semantic Web, Linked Data, natural language processing, computational linguistics, terminology, and information retrieval. It will also be of great interest to practitioners who are interested in re-examining their existing infrastructure and methodologies for handling multiple languages in Web applications or information retrieval systems.

Semantic Web. --- Semantic integration (Computer systems) --- Semantic networks (Information theory) --- World Wide Web --- Microformats --- Artificial intelligence. --- Computational linguistics. --- Information storage and retrieva. --- Computer science. --- Artificial Intelligence. --- Computational Linguistics. --- Information Storage and Retrieval. --- User Interfaces and Human Computer Interaction. --- Informatics --- Science --- Automatic language processing --- Language and languages --- Language data processing --- Linguistics --- Natural language processing (Linguistics) --- Applied linguistics --- Cross-language information retrieval --- Mathematical linguistics --- Multilingual computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data processing --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Information storage and retrieval. --- User interfaces (Computer systems). --- Interfaces, User (Computer systems) --- Human-machine systems --- Human-computer interaction --- Information organization. --- Information retrieval. --- Data retrieval --- Data storage --- Discovery, Information --- Information discovery --- Information storage and retrieval --- Retrieval of information --- Documentation --- Information science --- Information storage and retrieval systems --- Organization of information --- User interfaces (Computer systems)

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Computational linguistics --- Information retrieval --- Knowledge acquisition (Expert systems) --- Natural language processing (Computer science) --- Ontology --- Semantic Web

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Knowledge Management and Knowledge Engineering is a fascinating ?eld of re- 1 search these days. In the beginning of EKAW , the modeling and acquisition of knowledge was the privilege of - or rather a burden for - a few knowledge engineers familiar with knowledge engineering paradigms and knowledge rep- sentationformalisms.While the aimhasalwaysbeentomodelknowledgedecl- atively and allow for reusability, the knowledge models produced in these early days were typically used in single and very speci?c applications and rarely - changed. Moreover, these models were typically rather complex, and they could be understood only by a few expert knowledge engineers. This situation has changed radically in the last few years as clearly indicated by the following trends: - The creation of (even formal) knowledge is now becoming more and more collaborative. Collaborative ontology engineering tools and social software platforms show the potential to leverage the wisdom of the crowds (or at least of the many ) to lead to broader consensus and thus produce shared models which qualify better for reuse. - A trend can also be observed towards developing and publishing small but 2 3 4 high-impactvocabularies(e.g.,FOAF ,DublinCore ,GoodRelations)rather than complex and large knowledge models.

Information retrieval --- Office management --- Programming --- Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- applicatiebeheer --- apps --- informatica --- computerbesturingssystemen --- bedrijfsadministratie --- programmeren (informatica) --- informatiesystemen --- software engineering --- KI (kunstmatige intelligentie) --- computernetwerken --- architectuur (informatica) --- AI (artificiële intelligentie)

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Expert systems (Computer science). --- Expertsystemen. --- Information retrieval. --- Kennisverwerving. --- Knowledge acquisition (Expert systems). --- Ontologie. --- Ontology.