178 research outputs found

    Where Open Access Publishing is coming from and where it is going to

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    High efficiency realization for a wide-coverage unification grammar

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    We give a detailed account of an algorithm for efficient tactical generation from underspecified logical-form semantics, using a wide-coverage grammar and a corpus of real-world target utterances. Some earlier claims about chart realization are critically reviewed and corrected in the light of a series of practical experiments. As well as a set of algorithmic refinements, we present two novel techniques: the integration of subsumption-based local ambiguity factoring, and a procedure to selectively unpack the generation forest according to a probability distribution given by a conditional, discriminative model

    AIML and sequence-to-sequence models to build artificial intelligence chatbots: insights from a comparative analysis

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    A chatbot is a software that is able to autonomously communicate with a human being through text and due to its usefulness, an increasing number of businesses are implementing such tools in order to provide timely communication to their clients. In the past, whilst literature has focused on implementing innovative chatbots and the evaluation of such tools, limited studies have been done to critically comparing such conversational systems. In order to address this gap, this study critically compares the Artificial Intelligence Mark-up Language (AIML), and Sequence-to-Sequence models for building chatbots. In this endeavor, two chatbots were developed to implement each model and were evaluated using a mixture of glass box and black box evaluation, based on 3 metrics, namely, user’s satisfaction, the information retrieval rate, and the task completion rate of each chatbot. Results showed that the AIML chatbot ensured better user satisfaction, and task completion rate, while the Sequence-to-Sequence model had better information retrieval rate

    Automating the layout of network diagrams with specified visual organization

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    Geometric representations for minimalist grammars

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    We reformulate minimalist grammars as partial functions on term algebras for strings and trees. Using filler/role bindings and tensor product representations, we construct homomorphisms for these data structures into geometric vector spaces. We prove that the structure-building functions as well as simple processors for minimalist languages can be realized by piecewise linear operators in representation space. We also propose harmony, i.e. the distance of an intermediate processing step from the final well-formed state in representation space, as a measure of processing complexity. Finally, we illustrate our findings by means of two particular arithmetic and fractal representations.Comment: 43 pages, 4 figure

    The equivalence of four extensions of context-free grammars

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    There is currently considerable interest among computational linguists in grammatical formalisms with highly restricted generative power. This paper concerns the relationship between the class of string languages generated by several such formalisms, namely, combinatory categorial grammars, head grammars, linear indexed grammars, and tree adjoining grammars. Each of these formalisms is known to generate a larger class of languages than context-free grammars. The four formalisms under consideration were developed independently and appear superficially to be quite different from one another. The result presented in this paper is that all four of the formalisms under consideration generate exactly the same class of string languages
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