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Databases and Information Systems Commons

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Computer and Systems Architecture

Research Collection School Of Computing and Information Systems

2010

Articles 1 - 2 of 2

Full-Text Articles in Databases and Information Systems

A Self-Organizing Neural Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yu-Hong Feng, Yew-Soon Ong Mar 2010

A Self-Organizing Neural Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yu-Hong Feng, Yew-Soon Ong

Research Collection School Of Computing and Information Systems

This paper presents a self-organizing neural architecture that integrates the features of belief, desire, and intention (BDI) systems with reinforcement learning. Based on fusion Adaptive Resonance Theory (fusion ART), the proposed architecture provides a unified treatment for both intentional and reactive cognitive functionalities. Operating with a sense-act-learn paradigm, the low level reactive module is a fusion ART network that learns action and value policies across the sensory, motor, and feedback channels. During performance, the actions executed by the reactive module are tracked by a high level intention module (also a fusion ART network) that learns to associate sequences of actions …


Crctol: A Semantic Based Domain Ontology Learning System, Xing Jiang, Ah-Hwee Tan Jan 2010

Crctol: A Semantic Based Domain Ontology Learning System, Xing Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Domain ontologies play an important role in supporting knowledge‐based applications in the Semantic Web. To facilitate the building of ontologies, text mining techniques have been used to perform ontology learning from texts. However, traditional systems employ shallow natural language processing techniques and focus only on concept and taxonomic relation extraction. In this paper we present a system, known as Concept‐Relation‐Concept Tuple‐based Ontology Learning (CRCTOL), for mining ontologies automatically from domain‐specific documents. Specifically, CRCTOL adopts a full text parsing technique and employs a combination of statistical and lexico‐syntactic methods, including a statistical algorithm that extracts key concepts from a document collection, …