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.
This book explores recent advances in the integration of ontologies and lexical resources, including questions such as building the required infrastructure (e.g., the Semantic Web) and different formalisms, methods and platforms for eliciting, analyzing and encoding knowledge contents (e.g., multimedia, emotions, events, etc.). The contributors look towards next-generation technologies, shifting the focus from the state of the art to the future of Ontologies and Lexical Resources. This work will be of interest to research scientists, graduate students, and professionals in the fields of knowledge engineering, computational linguistics, and semantic technologies.
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.
Overview
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 ...