2012/10/29 by Tam T. Nguyen, Kuiyu Chang, Siu Cheung Hui · 1 voice · 2 citations
Computer Science · #Algorithms and Data Compression #Mathematics, Computing, and Information Processing #Natural Language Processing Techniques
paper · doi:10.1145/2396761.2396854
openalex publication_date 2012/10/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
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 Overflow, 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%.