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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Feel-Phy: An Intelligent Web-Based Physics QA System
verfasst von : Kwong Seng Fong, Chih How Bong, Zahrah Binti Ahmad, Norisma Binti Idris
Erschienen in: Soft Computing in Data Science
Verlag: Springer Singapore
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Abstract
Feel-Phy is a computerized and unmanned question answering system which is able to solve open-ended Physics problems, providing adaptive guidance and retrieve relevant resources to user inputs. Latent Semantic Indexing (LSI) is employed to process the user inputs and retrieve relevant references. The proposed architecture for Feel-Phy constitutes of four basic modules: data extraction, question classification, solution identification and answer formulation. The data extraction module is used to construct a Physics knowledge base. The question classification module is used to identify question type and understand the question. The solution identification module computes the answer to the question and also retrieve the top n most relevant resource references to the users. Finally, the last module, answer formulation is to present the results to the users. Our preliminary experiments have shown that this proposed method is able to solve well-structure Physics question and retrieve relevant references to the users.