Feel-Phy: An Intelligent Web-Based Physics QA System
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.
KeywordsLSI QA system Calculation Information retrieval Physics problem Open text question
This research is supported by research grant RACE/b(6)/1098/2013(06), KPM. Besides, I would like to express my deepest gratitude to my supervisor, Dr. Bong Chih How for his extraordinary efforts in providing guidance and motivation. Besides, I also want to thank Associate Prof. Dr. Zahrah Binti Ahmad and Dr. Norisma Binti Idris for suggesting a lot of ideas and comments about the system in order to improve my system. I also wish to take this opportunity to acknowledge my heartiest thanks to all my friends who involved directly or indirectly towards the accomplishment of my system.
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