Browsing by Author "Maldeniya, MKDT"

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    item: Conference-Extended-Abstract
    An assessment of mobile network big data-based insights for transport planning in Sri Lanka
    (Sri Lanka Society for Transport and Logistics, 2016-06) Maldeniya, MKDT; Lokanathan, S; Kumarage, AS; Gunaruwan, TL
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    item: Conference-Full-text
    Mapping dependency relationships into semantic frame relationships
    (Computer Science & Engineering Society c/o Department of Computer Science and Engineering, University of Moratuwa., 2011-11) de Silva, NHND; Fernando, CSNJ; Maldeniya, MKDT; Wijeratne, DNC; Perera, AS; Goertzel, B; Weerawardhana, S; Madusanka, A; Dilrukshi, T; Aravinda, H
    We describe the refactoring process of the Natural Language Understanding pipeline of OpenCog Artificial General Intelligence Framework, a method for expanding the concept ontology of the pipeline using statistical learning algorithms. Further an experimental approach to automatically generating a common sense knowledge base specifically with relation to concept relationships derived from the natural language pipeline using data mining techniques is detailed and evaluated.
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    item: Conference-Abstract
    SeMap - mapping dependency relationships into semantic frame relationships
    (2011) Fernando, CSNJ; Maldeniya, MKDT; Wijeratne, DNC; Perera, AS; Goertze, B; De Silva, NHND
    We describe the refacloring process of the RelEx2Frame component of OpenCog AGI Framework, a method for expanding concept variables used in RelEx and automatic generation of a common sense knowledge base specifically with relation to concept relationships. The well-known Drools rule engine is used instead of handcoded rides; an asynchronous concurrent architecture and an indexing mechanism are designed to gain performance of re-factored RelEx2Frame. WordNet aided supervised learning mechanism is applied to expand concept variables. Association mining is used on semantic frames acquired through processing an instance of Wikipedia in order to generate a common sense knowledge base.
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    item: Conference-Abstract
    Semi-supervised algorithm for concept ontology based word set expansion
    (2014-06-26) De Silva, NHND; Perera, AS; Maldeniya, MKDT
    Word lists that contain closely related sets of words is a critical requirement in machine understanding and processing of natural languages. Creating and maintaining such closely related word lists is a critical and complex process that requires human input and carried out manually in the absence of tools. We describe a supervised learning mechanism which employs a word ontology to expand word lists containing closely related sets of words. The approach described in this paper uses two novel supervised learning techniques that complement each other for the purpose of expanding existing lists of related words. Expanding concept variable lists of RelEx2Frame component of OpenCog Artificial General Intelligence Framework using WordNet is used as a proof of concept. Intervention of this project would enable OpenCog applications to attempt to understand words that they were not able to understand before, due to the limited size of existing lists of related words.