MQL: A Mathematical Formula Query Language for Mathematical Search

Guo, Wenfei; Su, Wei; Li, Lian; An, Ning; Cui, Linwei

doi:10.1109/cse.2011.52

Cited by 4 publications

(4 citation statements)

References 13 publications

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“…There are several typical searching systems with math retrieval function. For example, Digital Library of Mathematical Functions (DLMF) search [1][2][3][4], MathDex [5], MathWebSearch [6-8], LeActiveMath [9][10][11], EgoMath [12][13][14][15], Mathsearch [16][17][18], et al These systems could be divided into two classes according to their matching structures: full-text searching based methods and special designed retrieval methods. The former, including DLMF Search, MathDex, LeActiveMath and Egomath, established their math searching functions on the basis of traditional full-text searching technology through transforming mathematical expressions into text string.…”

Section: Related Workmentioning

confidence: 99%

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A matching model of mathematical expressions with FDS based index

Yang

Tian

et al. 2015

Int. J. Mach. Learn. & Cyber.

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Mathematical expression retrieval is a key means of searching scientific contents in web and digital libraries. Because mathematical expressions have many different attributes compared with ordinary text, it is necessary to study the special retrieval methods including the indexing and matching model of mathematical expressions. In this paper, on the basis of the introduction of the existing math searching methods and the FDS based index, a mathematical expression matching model was proposed which realized the exact matching of formulas with three query modes called global query mode, local query mode and operational query mode. The algorithms of the query modes were given respectively. A prototype system based on the proposed model was implemented and the comparison experiments were carried out. The experimental results show that the proposed matching model simultaneously realized matching formulas in exact mode and reducing time and space consumption of retrieving to an acceptable degree. It is effective for searching math content in relative digital mathematics library.

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Section: Related Workmentioning

confidence: 99%

“…Its indexing and matching mechanism was based on Lucene architecture with proper modification from full text to formulas. They built two kinds of indexes called content-based index and presentation-based index to make users search mathematical information on presentation level and meaningful level [16][17][18].…”

Section: Related Workmentioning

confidence: 99%

A matching model of mathematical expressions with FDS based index

Yang

Tian

et al. 2015

Int. J. Mach. Learn. & Cyber.

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“…However, the traditional full-text retrieval model for one-dimensional is not effective when facing the special two-dimensional pattern retrieval of mathematical expressions. At present, research studies on mathematical expression retrieval and ranking have been carried out with some progress, and methods and prototype systems [1][2][3][4][5][6] with mathematical retrieval functions have been proposed.…”

Section: Introductionmentioning

confidence: 99%

A Multimodal Retrieval and Ranking Method for Scientific Documents Based on HFS and XLNet

Yan

Shi

et al. 2022

Scientific Programming

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Aiming at the defects of traditional full-text retrieval models in dealing with mathematical expressions, which are special objects different from ordinary texts, a multimodal retrieval and ranking method for scientific documents based on hesitant fuzzy sets (HFS) and XLNet is proposed. This method integrates multimodal information, such as mathematical expression images and context text, as keywords to realize the retrieval of scientific documents. In the image modal, the images of mathematical expressions are recognized, and the hesitancy fuzzy set theory is introduced to calculate the hesitancy fuzzy similarity between mathematical query expressions and the mathematical expressions in candidate scientific documents. Meanwhile, in the text mode, XLNet is used to generate word vectors of the mathematical expression context to obtain the similarity between the query text and the mathematical expression context of the candidate scientific documents. Finally, the multimodal evaluation is integrated, and the hesitation fuzzy set is constructed at the document level to obtain the final scores of the scientific documents and corresponding ranked output. The experimental results show that the recall and precision of this method are 0.774 and 0.663 on the NTCIR dataset, respectively, and the average normalized discounted cumulative gain (NDCG) value of the top-10 ranking results is 0.880 on the Chinese scientific document (CSD) dataset.

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“…In this system, Mathematical formula Query Language (MQL) [16] was designed for expressing and processing query. MQL contains two forms: a character string form (MQLS) and XML form (MQLX).…”

Section: Related Workmentioning

confidence: 99%

A Semantic Approach for Mathematical Expression Retrieval

Asebriy¹,

Kaloun²,

Raghay³

et al. 2016

ijacsa

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Abstract-Math search or mathematical expression retrieval has become a challenging task. Mathematical expressions are very complex, they are highly symbolic, and they have a semantic meaning that we should respect. In this paper, we propose a similarity search method for mathematical expression based on a multilevel representation of expressions and a multilevel search. We used the K-Nearest Neighbors with three types of distances to evaluate relevance between expressions. In the experimental level, the proposed system significantly outperforms statistical algorithms.

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MQL: A Mathematical Formula Query Language for Mathematical Search

Cited by 4 publications

References 13 publications

A matching model of mathematical expressions with FDS based index

A matching model of mathematical expressions with FDS based index

A Multimodal Retrieval and Ranking Method for Scientific Documents Based on HFS and XLNet

A Semantic Approach for Mathematical Expression Retrieval

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