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Other titles in the Theory and Applications of Natural Language Processing series:
New Trends of Research in Ontologies and Lexical Resources: Ideas, Projects, Systems (Theory and Applications of Natural Language Processing)
Synopses & Reviews
This book is about the role of knowledge in information systems. Knowledge is usually articulated and exchanged through human language(s). In this sense, language can be seen as the most natural vehicle to convey our concepts, whose meanings are usually intermingled, grouped and organized according to shared criteria, from simple perceptions ("every tree has a stem") and common sense ("unsupported objects fall") to complex social conventions ("a tax is a fee charged by a government on a product, income, or activity"). But what is natural for a human being turns out to be extremely difficult for machines: machines need to be instilled with knowledge and suitably equipped with logical and statistical algorithms to reason over it. Computers can't represent the external world and communicate their representations as effectively as humans do: ontologies and NLP have been invented to face this problem: in particular, integrating ontologies with (possibly multi-lingual) computational lexical resources is an essential requirement to make human meanings understandable by machines. This book explores the advancements in this integration, from the most recent steps in building the necessary infrastructure, i.e. the Semantic Web, to the different knowledge contents that can be analyzed, encoded and transferred (multimedia, emotions, events, etc.) through it. The work aims at presenting the progress in the field of integrating ontologies and lexicons: together, they constitute the essential technology for adequately represent, elicit and exchange knowledge contents in information systems, web services, text processing and several other domains of application.
Surveying new directions of research and development in the interdisciplinary framework where ontologies and lexical resources intersect, this book deals with the complex relation between lexicons (in different languages) and the underlying ontological model.
In order to exchange knowledge, humans need to share a common lexicon of words as well as to access the world models underlying that lexicon. What is a natural process for a human turns out to be an extremely hard task for a machine: computers can't represent knowledge as effectively as humans do, which hampers, for example, meaning disambiguation and communication. Applied ontologies and NLP have been developed to face these challenges. Integrating ontologies with (possibly multilingual) lexical resources is an essential requirement to make human language understandable by machines, and also to enable interoperability and computability across information systems and, ultimately, in the Web.
As human linguistic practice reveals, accessing to concepts through natural language is the implicit pathway for enabling mutual comprehension and effective meaning negotiation between agents in a community. But, in order to exchange knowledge, we need to share the conceptual models underlying the lexicon, namely ontologies. These remarks become even more crucial when focusing on human-computer interaction. In this context, computational ontologies and human-language technologies converge in the task of providing the semantic description of knowledge contents (e.g. multimedia, web resources, services, etc.): underlying intended models need to be made explicit in order to become accessible by artificial agents and sharable with humans. According to this picture: 1) computational lexicons constitute a fundamental component to foster the (mono- and multi-linguistic) access to any knowledge content; 2) computational ontologies, on the other side, are necessary to capture the logical structure of those knowledge contents: both contribute to dig out the basic elements of a given semantic space, characterizing the different relations holding among them.
Table of Contents
1.Introduction.- A.Oltramari, L.Qin, P.Vossen, E.Hovy.- Part I Achieving the Interoperability of Linguistic Resources in the Semantic Web.- 2.Towards Open Data for Linguistics: Linguistic Linked Data. C.Chiarcos, J.McCrae, P.Cimiano, and C.Fellbaum.- 3.Establishing Interoperability between Linguistic and Terminological Ontologies. W.Peters.- 4.On the Role of Senses in the Ontology-Lexicon. P.Cimiano, J.McCrae, P.Buitelaar, E.Montiel-Ponsoda.- Part II Event Analysis from Text and Multimedia.- 5.KYOTO: a Knowledge-rich Approach to the Interoperable Mining of Events From Text. P.Vossen, E.Agirre, G.Rigau and A.Soroa.- 6.Anchoring Background Knowledge to Rich Multimedia Contexts in the KNOWLEDGESTORE. R. Cattoni, F. Corcoglioniti, C. Girardi, B. Magnini, L. Serafini, and R. Zanoli.- 7.Lexical Mediation for Ontology-based Annotation of Multimedia. M.Cataldi, R.Damiano, V.Lombardo and A.Pizzo.- 8.Knowledge in Action: Integrating Cognitive Architectures and Ontologies. A.Oltramari, C.Lebiere.- Part III Enhancing NLP with Ontologies.- 9.Use of Ontology, Lexicon and Fact Repository for Reference Resolution in Ontological Semantics. M.McShane and S.Nirenburg.- 10.Ontology-based Semantic Interpretation via Grammar Constraints. S.Muresan.- 11.How Ontology Based Information Retrieval Systems may Benefit from Lexical Text Analysis. S.Ranwez, B.Duthil, M.F.Sy, J.Montmain, P.Augereau and V.Ranwez.- Part IV Sentiment Analysis thorugh Lexicon and Ontologies.- 12.Detecting Implicit Emotion Expressions from Text Using Ontological Resources and Lexical Learning. A.Balahur, J.M. Hermida and H.Tanev.- 13.The Agile Cliché: Using Flexible Stereotypes as Building Blocks in the Construction of an Affective Lexicon. T.Veale.
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