7,488 research outputs found

    Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar

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    A usage-based Construction Grammar (CxG) posits that slot-constraints generalize from common exemplar constructions. But what is the best model of constraint generalization? This paper evaluates competing frequency-based and association-based models across eight languages using a metric derived from the Minimum Description Length paradigm. The experiments show that association-based models produce better generalizations across all languages by a significant margin

    Issues with Evaluating and Using Publicly Available Ontologies

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    The proliferation of ontologies in the public domain and the ease of accessing them offers new opportunities for knowledge sharing and interoperability in an open, distributed environment, but it also poses interesting challenges for knowledge and Web engineers alike. In this paper we discuss and analyse those challenges with emphasis on the need to evaluate publicly available ontologies prior to use. We elaborate on a number of issues ranging from technological concerns to strategic and political issues. We drawn our experiences from the field of ontology mapping on the Semantic Web, a necessity that enables many of Semantic Web's proclaimed features

    Foreground and background text in retrieval

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    Our hypothesis is that certain clauses have foreground functions in text, while other clauses have background functions and that these functions are expressed or reflected in the syntactic structure of the clause. Presumably these clauses will have differing utility for automatic approaches to text understanding; a summarization system might want to utilize background clauses to capture commonalities between numbers of documents while an indexing system might use foreground clauses in order to capture specific characteristics of a certain document

    Extracting Spooky-activation-at-a-distance from Considerations of Entanglement

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    Following an early claim by Nelson & McEvoy \cite{Nelson:McEvoy:2007} suggesting that word associations can display `spooky action at a distance behaviour', a serious investigation of the potentially quantum nature of such associations is currently underway. This paper presents a simple quantum model of a word association system. It is shown that a quantum model of word entanglement can recover aspects of both the Spreading Activation equation and the Spooky-activation-at-a-distance equation, both of which are used to model the activation level of words in human memory.Comment: 13 pages, 2 figures; To appear in Proceedings of the Third Quantum Interaction Symposium, Lecture Notes in Artificial Intelligence, vol 5494, Springer, 200
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