Research Papers - Dept of Information Technology

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Subject: search.filters.subject.Methodology

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    Methodology of knowledge representation from natural language (Onto_X)
    (IEEE, 2013-04-26) Koggalahewa, D. N; Amararachchi, J. L; Pilapitiya, S. U; Geegange, D. T. K
    Information available in different formats cannot be understood by a computer or a machine due to lack of a proper knowledge representation mechanism. It always requires more human effort in feeding the knowledge to the computers or the knowledgebase. XML covers the basic level of knowledge representation, but is incapable of utilizing the concepts and semantics in a proper way. Onto_X is an effort made to automate the process of ontology construction from an annotated xml file or database. The annotation process is done by any natural language processing tool (apart from the system). The system requires an xml file as the input and converts it into ontology in owl format. The system is capable of generating the semantics over annotated content with owl components. XML entities will be automatically mapped into the owl components such as classes, sub classes, instances and relationships. The conversion mechanism is totally automated inside the Onto_X since it assures all the co-relationships over the annotated content. The conversion process identifies the xml properties and assigns semantics with the integration of word-net 2.1 and owl properties over the parsed content. The system uses the protege libraries for the conversion process. The most special feature in the conversion process is that it uses its own inference, without just mapping xml properties to owl. The system is capable of visualizing the mapped owl ontology and it allows the user to refine the content of the constructed ontology. The final outcome of the system is ontology in owl format, which is mapped from the xml file or a database. The research ensures a better knowledge representation mechanism and it will assure the creation of domain knowledge from the xml file. The expandability is high since it takes information from the base level.
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    Methodology for coping with uncertain information contained in natural language instructions in a robotic system
    (IEEE, 2020-12-10) Bandara, H. M. Y. L. W; Wijesekera, D. S; Bandara Herath, H. M. T. D; Kodagoda, D. L; Rajapaksha, S, K
    Intelligent service robots are currently being developed to provide services and assistance in different sectors including domestic and household context. Typically, the service tasks of a domestic service robot involve direct interaction with humans. Humans typically express their ideas through voice communication. However, communication through natural language is imprecise because it tends to contain uncertain and unknown information. Therefore, understanding uncertain terms contained in natural language is a crucial capability that an intelligent service robot should possess. Hence, this project which is named as IntelBot is aimed at developing a methodology to cope with uncertain and unknown words contained in a natural language command given to a domestic service robot. In brief, the proposed system can interpret uncertain commands related to speed such as “go very fast” and the uncertain commands related to time such as “go later”. Additionally, if the robot is instructed to identify an object which is regarded to be unknown, as an example “cup” it can interpret and identify that particular object. And for the entire system, a user-friendly interface is developed for the easy control of the robot and the demonstration of the functionalities.