Common Sense Reasoning
PI: Surangika Ranathunga
The Common Sense Reasoning project focuses on advancing culturally grounded evaluation and knowledge representation for language-based artificial intelligence systems.

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 rulses; 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.
Keywords: Natural Language Processing | Machine Learning / Deep Learning | Ontologies | WordNet | Rule-based | Common Sense Reasoning |
@inproceedings{fernando2013semap,
title={{SeMap-Mapping Dependency Relationships into Semantic Frame Relationships}},
author={de Silva, N. H. N. D. and Fernando, C. S. N. J. and Maldeniya, M. K. D. T. and Wijeratne, D. N. C. and Perera, A. S. and Goertzel, B},
booktitle={Proceedings of the Engineering Research Unit Symposium},
month={12},
year={2011},
abstract={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 rulses; 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.},
misc={https://goo.gl/9kWThV,NLP:ML:ONT,https://i1.rgstatic.net/publication/269466145_SeMap_-_Mapping_Dependency_Relationships_into_Semantic_Frame_Relationships/links/5948ffef458515db1fdb3770/largepreview.png}
}
PI: Surangika Ranathunga
The Common Sense Reasoning project focuses on advancing culturally grounded evaluation and knowledge representation for language-based artificial intelligence systems.
PI: Nisansa de Silva
The Knowledge Representation project investigates methods for structuring, aligning, and reasoning over knowledge extracted from language, with particular emphasis on low-resource settings, domain-specific semantics, and intelligent information access.