Thesis (Ph.D.)--Aberdeen University, 2008. / Title from web page (viewed on July 23, 2009). Includes bibliographical references.

Thesis (M.F.A.)--Kent State University, 2009. / Title from PDF t.p. (viewed April 22, 2010). Advisor: Sanda Katila. Keywords: microformats; semantic web; labels. Includes bibliographical references (p. 52-53).

Habil.-Schr., Univ. St. Gallen, 2007.

This thesis provides a detailed description of the research undertaken into the creation of a framework that uses Semantic Web languages to implement a recently developed commonsense reasoning formalism called Discrete Event Calculus (DEC). It aims to show to what extent DEC reasoning can be applied to Semantic Web data, using the Semantic Web standards and supporting development environments available for the purpose in 2008, when the research programme commenced. The research aims to provide an accurate and reusable DEC ontology using the languages defined in Semantic Web Standards. To this end, an ontology describing the DEC entities and axioms is defined in OWL and SWRL; this represents the core elements of the DEC formalism, namely its set of logical types and predicates and the relations between them. The ontology is used together with a proof-of-concept DEC resolver software that applies the ontology to an existing rules engine, so that new inferences can be created from a DEC domain. The design and implementation of the combined ontology and software framework are described in detail. The methodological issues involved in reconciling a software model with an ontology model are also discussed and the capabilities of the framework are validated by a series of tests modelled on established AI benchmark scenarios that can be resolved correctly using DEC. The results confirm that the framework will create the appropriate inferences with reference to the benchmark problems, though they also highlight some of current limitations in the framework, notably to do with how it represents changing fluent values. A detailed sample domain ontology is provided, which is based on the domain of turn-based multiplayer online games; this illustrates how the DEC ontology defined in this research could be extended for use with other domains. A further extension of the DEC ontology is proposed, which enables the resolver to represent real-world time values independently of the timepoints defined as part of the formalism. Finally, the strengths and extant boundaries of the chosen approach are discussed and suggestions are provided for improvements that could form the basis of future work.

No description available.

While pragmatics, through its integration of situational awareness and real world relevant knowledge, offers a high level of analysis that is suitable for real interpretation of natural dialogue, semantics, on the other end, represents a lower yet more tractable and affordable linguistic level of analysis using current technologies. Generally, the understanding of semantic meaning in literature has revolved around the famous quote ``You shall know a word by the company it keeps''. In this thesis we investigate the role of context constituents in decoding the semantic meaning of the engulfing context; specifically we probe the role of salient concepts, defined as content-bearing expressions which afford encyclopedic definitions, as a suitable source of semantic clues to an unambiguous interpretation of context. Furthermore, we integrate this world knowledge in building a new and robust unsupervised semantic model and apply it to entail semantic relatedness between textual pairs, whether they are words, sentences or paragraphs. Moreover, we explore the abstraction of semantics across languages and utilize our findings into building a novel multi-lingual semantic relatedness model exploiting information acquired from various languages. We demonstrate the effectiveness and the superiority of our mono-lingual and multi-lingual models through a comprehensive set of evaluations on specialized synthetic datasets for semantic relatedness as well as real world applications such as paraphrase detection and short answer grading. Our work represents a novel approach to integrate world-knowledge into current semantic models and a means to cross the language boundary for a better and more robust semantic relatedness representation, thus opening the door for an improved abstraction of meaning that carries the potential of ultimately imparting understanding of natural language to machines.

Currently, the data provided by the heterogeneous buoy sensors/networks (e.g. National Data Buoy center (NDBC), Gulf Of Maine Ocean Observing System (GoMoos) etc. is not amenable to the development of integrated systems due to conflicts in the data representation at syntactic and structural levels. With the rapid increase in the amount of information, the integration of heterogeneous resources is an important issue and requires integrative technologies such as semantic web. In distributed data dissemination system, normally querying on single database will not provide relevant information and requires querying across interrelated data sources to retrieve holistic information. In this thesis we develop system for integrating two different Resource Description Framework (RDF) data sources through intelligent querying using Simple Protocol and RDF Query Language (SPARQL). We use Semantic Web application framework from AllegroGraph that provides functionality for developing triple store for the ontological representations, forming federated stores and querying it through SPARQL.

No description available.

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In Web service composition, service discovery and combining suitable services through determination of interoperability among different services are important operations. Utilizing semantics improves the quality and facilitates automation of these operations. There are several previous approaches for semantic service discovery and service matching. In this work, we exploit and extend these semantic approaches in order to make Web service composition process more facilitated, less error prone and more automated. This work includes a service discovery and service interoperability checking technique which extends the previous semantic matching approaches. In addition to this, as a guidance system for the user, a new semantic domain model is proposed that captures semantic relations between concepts in various ontologies.