Mathematical Document Retrieval for Problem Solving

Author

Samarasinghe, Sidath Harshanath ; Hui, Siu Cheung

Author_Institution

Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore

Volume

1

fYear

2009

fDate

22-24 Jan. 2009

Firstpage

583

Lastpage

587

Abstract

Solving mathematical problems is both challenging and difficult for many students. This paper proposes a document retrieval approach to help solve mathematical problems. The proposed approach is based on Kohonenpsilas Self-Organizing Maps for data clustering of similar mathematical documents from a mathematical document database. Based on a user query problem, similar mathematical documents with their associated solutions are retrieved in order to provide hints or solutions on solving the user problem. In this paper, we will discuss the proposed mathematical document retrieval approach. The performance of the proposed approach will also be presented in comparison with other clustering techniques.

Keywords

computer aided instruction; data mining; mathematics computing; pattern clustering; query processing; self-organising feature maps; Kohonen self-organizing map; data clustering; data mining; mathematical document database; mathematical document retrieval; problem solving; query problem; Artificial intelligence; Clustering algorithms; Data engineering; Data mining; Databases; Neural networks; Partitioning algorithms; Problem-solving; Search engines; Self organizing feature maps; Artificial Intelligence; Data Mining; Knowledge Data Engineering;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering and Technology, 2009. ICCET '09. International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-3334-6

Type

conf

DOI

10.1109/ICCET.2009.69

Filename

4769534