2,597 research outputs found

    Ontology learning for the semantic deep web

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    Ontologies could play an important role in assisting users in their search for Web pages. This dissertation considers the problem of constructing natural ontologies that support users in their Web search efforts and increase the number of relevant Web pages that are returned. To achieve this goal, this thesis suggests combining the Deep Web information, which consists of dynamically generated Web pages and cannot be indexed by the existing automated Web crawlers, with ontologies, resulting in the Semantic Deep Web. The Deep Web information is exploited in three different ways: extracting attributes from the Deep Web data sources automatically, generating domain ontologies from the Deep Web automatically, and extracting instances from the Deep Web to enhance the domain ontologies. Several algorithms for the above mentioned tasks are presented. Lxperimeiital results suggest that the proposed methods assist users with finding more relevant Web sites. Another contribution of this dissertation includes developing a methodology to evaluate existing general purpose ontologies using the Web as a corpus. The quality of ontologies (QoO) is quantified by analyzing existing ontologies to get numeric measures of how natural their concepts and their relationships are. This methodology was first applied to several major, popular ontologies, such as WordNet, OpenCyc and the UMLS. Subsequently the domain ontologies developed in this research were evaluated from the naturalness perspective

    Computational Ontologies and Information Systems II: Formal Specification

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    This paper extends the study of ontologies in Part I of this study (Volume 14, Article 8) in the context of Information Systems. The basic foundations of computational ontologies presented in Part I are extended to formal specifications in this paper. This paper provides a review of the formalisms, languages, and tools for specifying and implementing computational ontologies Directions for future research are also provided

    Production of Referring Expressions for an Unknown Audience : a Computational Model of Communal Common Ground

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    The research reported in this article is based on the Ph.D. project of Dr. RK, which was funded by the Scottish Informatics and Computer Science Alliance (SICSA). KvD acknowledges support from the EPSRC under the RefNet grant (EP/J019615/1).Peer reviewedPublisher PD

    Creationism and evolution

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    In Tower of Babel, Robert Pennock wrote that “defenders of evolution would help their case immeasurably if they would reassure their audience that morality, purpose, and meaning are not lost by accepting the truth of evolution.” We first consider the thesis that the creationists’ movement exploits moral concerns to spread its ideas against the theory of evolution. We analyze their arguments and possible reasons why they are easily accepted. Creationists usually employ two contradictive strategies to expose the purported moral degradation that comes with accepting the theory of evolution. On the one hand they claim that evolutionary theory is immoral. On the other hand creationists think of evolutionary theory as amoral. Both objections come naturally in a monotheistic view. But we can find similar conclusions about the supposed moral aspects of evolution in non-religiously inspired discussions. Meanwhile, the creationism-evolution debate mainly focuses — understandably — on what constitutes good science. We consider the need for moral reassurance and analyze reassuring arguments from philosophers. Philosophers may stress that science does not prescribe and is therefore not immoral, but this reaction opens the door for the objection of amorality that evolution — as a naturalistic world view at least — supposedly endorses. We consider that the topic of morality and its relation to the acceptance of evolution may need more empirical research

    Survey on Evaluation Methods for Dialogue Systems

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    In this paper we survey the methods and concepts developed for the evaluation of dialogue systems. Evaluation is a crucial part during the development process. Often, dialogue systems are evaluated by means of human evaluations and questionnaires. However, this tends to be very cost and time intensive. Thus, much work has been put into finding methods, which allow to reduce the involvement of human labour. In this survey, we present the main concepts and methods. For this, we differentiate between the various classes of dialogue systems (task-oriented dialogue systems, conversational dialogue systems, and question-answering dialogue systems). We cover each class by introducing the main technologies developed for the dialogue systems and then by presenting the evaluation methods regarding this class

    Can humain association norm evaluate latent semantic analysis?

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    This paper presents the comparison of word association norm created by a psycholinguistic experiment to association lists generated by algorithms operating on text corpora. We compare lists generated by Church and Hanks algorithm and lists generated by LSA algorithm. An argument is presented on how those automatically generated lists reflect real semantic relations
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