The Ontology Of Music Groups
Download The Ontology Of Music Groups PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get The Ontology Of Music Groups book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
The Ontology of Music Groups
This volume examines the ontology of music groups. It connects two fascinating areas of philosophical research: the ontology of social groups and the philosophy of music. Interest in questions about the nature of music groups is growing. Since people are widely familiar with music groups, the topic is particularly well-suited for introducing issues in social ontology. Being comparably small-scale and temporary, music groups also provide an excellent case study for those who think that social groups are analyzed best by considering small groups. The present volume provides a comprehensive overview of the topic and seeks to establish the ontology of music groups as a distinct field of philosophical research. The chapters, written by leading scholars working on social ontology, revolve around four core themes: The identity of music groups Variations between different kinds of music groups The persistence and longevity of (different kinds of) music groups Various characteristics of music groups, including their rational and emotional aspects, as well as their creative abilities The contributors consider these themes across a wide range of music groups, including popular music groups, rock bands, alternative acts, hip hop crews, choirs and classical orchestras. The Ontology of Music Groups will appeal to scholars and advanced students working in social ontology, metaphysics, and the philosophy of music.
Knowledge Engineering: Practice and Patterns
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.
Engineering Background Knowledge for Social Robots
Social robots are embodied agents that perform knowledge-intensive tasks involving several kinds of information from different heterogeneous sources. This book, Engineering Background Knowledge for Social Robots, introduces a component-based architecture for supporting the knowledge-intensive tasks performed by social robots. The design was based on the requirements of a real socially-assistive robotic application, and all the components contribute to and benefit from the knowledge base which is its cornerstone. The knowledge base is structured by a set of interconnected and modularized ontologies which model the information, and is initially populated with linguistic, ontological and factual knowledge retrieved from Linked Open Data. Access to the knowledge base is guaranteed by Lizard, a tool providing software components, with an API for accessing facts stored in the knowledge base in a programmatic and object-oriented way. The author introduces two methods for engineering the knowledge needed by robots, a novel method for automatically integrating knowledge from heterogeneous sources with a frame-driven approach, and a novel empirical method for assessing foundational distinctions over Linked Open Data entities from a common-sense perspective. These effectively enable the evolution of the robot’s knowledge by automatically integrating information derived from heterogeneous sources and the generation of common-sense knowledge using Linked Open Data as an empirical basis. The feasibility and benefits of the architecture have been assessed through a prototype deployed in a real socially-assistive scenario, and the book presents two applications and the results of a qualitative and quantitative evaluation.