A math-aware search engine for math question answering system
We propose a math-aware search engine that is capable of handling both textual keywords as well as mathematical expressions. Our math feature extraction and representation framework captures the semantics of math expressions via a Finite State Machine model. We adapt the passive aggressive onli...
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sg-ntu-dr.10356-979602020-05-28T07:18:08Z A math-aware search engine for math question answering system Chang, Kuiyu Hui, Siu Cheung Nguyen, Tam T. School of Computer Engineering International conference on Information and knowledge management (21st : 2012 : Maui, USA) We propose a math-aware search engine that is capable of handling both textual keywords as well as mathematical expressions. Our math feature extraction and representation framework captures the semantics of math expressions via a Finite State Machine model. We adapt the passive aggressive online learning binary classifier as the ranking model. We benchmarked our approach against three classical information retrieval (IR) strategies on math documents crawled from Math Over ow, a well-known online math question answering system. Experimental results show that our proposed approach can perform better than other methods by more than 9%. 2013-07-25T07:37:53Z 2019-12-06T19:48:49Z 2013-07-25T07:37:53Z 2019-12-06T19:48:49Z 2012 2012 Conference Paper Nguyen, T. T., Chang, K., & Hui, S. C. (2012). A math-aware search engine for math question answering system. Proceedings of the 21st ACM international conference on Information and knowledge management. https://hdl.handle.net/10356/97960 http://hdl.handle.net/10220/12277 10.1145/2396761.2396854 en © 2012 ACM. |
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Nanyang Technological University |
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NTU Library |
country |
Singapore |
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English |
description |
We propose a math-aware search engine that is capable of
handling both textual keywords as well as mathematical expressions.
Our math feature extraction and representation
framework captures the semantics of math expressions via a
Finite State Machine model. We adapt the passive aggressive
online learning binary classifier as the ranking model.
We benchmarked our approach against three classical information
retrieval (IR) strategies on math documents crawled
from Math Over ow, a well-known online math question answering
system. Experimental results show that our proposed
approach can perform better than other methods by
more than 9%. |
author2 |
School of Computer Engineering |
author_facet |
School of Computer Engineering Chang, Kuiyu Hui, Siu Cheung Nguyen, Tam T. |
format |
Conference or Workshop Item |
author |
Chang, Kuiyu Hui, Siu Cheung Nguyen, Tam T. |
spellingShingle |
Chang, Kuiyu Hui, Siu Cheung Nguyen, Tam T. A math-aware search engine for math question answering system |
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Chang, Kuiyu |
title |
A math-aware search engine for math question answering system |
title_short |
A math-aware search engine for math question answering system |
title_full |
A math-aware search engine for math question answering system |
title_fullStr |
A math-aware search engine for math question answering system |
title_full_unstemmed |
A math-aware search engine for math question answering system |
title_sort |
math-aware search engine for math question answering system |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/97960 http://hdl.handle.net/10220/12277 |
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1681056214841032704 |