An indexing method of mathematical expression retrieval

Tian, Xuedong; Yang, Songqiang; Li, Xinfu; Yang, Fang

doi:10.1109/iccsnt.2013.6967179

Cited by 8 publications

(7 citation statements)

References 7 publications

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“…Each group of evaluation attributes contains multiple evaluation indicators. e similarity of the analytical mathematical expression of FDS [11,12] is calculated by the hesitant fuzzy set.…”

Section: Mathematical Expression Image Similaritymentioning

confidence: 99%

“…In the research of mathematical expression retrieval and ranking that fuses mathematical expressions with textual information, MIaS [9] used the LRO (Leave Rightmost Out) method to split the original query generated by the combination of keywords and mathematical expressions into subqueries and merged the results using appropriate weighting to obtain more relevant results to the original topic. Zai and Tian [10] used FDS [11,12] to parse the formulas and retrieved relevant documents using obtained operators.…”

Section: Introductionmentioning

confidence: 99%

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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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“…Each group of evaluation attributes contains multiple evaluation indicators. e similarity of the analytical mathematical expression of FDS [11,12] is calculated by the hesitant fuzzy set.…”

Section: Mathematical Expression Image Similaritymentioning

confidence: 99%

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

Self Cite

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“…FDS based math index [22] integrated inverted index used in full-text search engine [23] with FDS attributes of formula symbols. It is composed of two tables: indexed table and inverted table. Indexed table consists of the items in the form of (S i , N i ), where S i is the ith symbol and N i is the number of the expressions which contain S i .…”

Section: Definition Of Fds Based Indexmentioning

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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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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“…Suppose that the mathematical expressions are described in LaTeX format. Take the FDS (Formula Description Structure) defined in [20] [21] as the basis of the retrieval feature of mathematical expressions.  Flag stores the relationship between current item and its control item which has the higher level in the formulae.…”

Section: Feature Extraction Of Mathematical Expressionsmentioning

confidence: 99%

An Improved Indexing and Matching Method for Mathematical Expressions Based on Inter-Relevant Successive Tree

Baoding¹

2016

JCC

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In recent years, a growing number of math contents are available on the Web. When conventional search engines deal with mathematical expressions, the two-dimensional structure of mathematical expressions is lost, which results in a low performance of math retrieval. While the retrieval technology specifically designed for mathematical expressions is not mature currently. Aiming at these problems, an improved mathematical expression indexing and matching method was proposed through employing full text index method to deal with the two-dimensional structure of mathematical expressions. Firstly, through the fully consideration of LaTeX formulae' characteristics, a feature representation method of mathematical expressions and a clustering method of feature keywords were put forward. Then, an improved inter-relevant successive trees index model was applied to the construction of the mathematical expression index, in which the cluster algorithm of mathematical expression features was employed to solve the problem of the quantity growth of the trees in processing large amount of formulae. Finally, the matching algorithms of mathematical expressions were given which provide four query modes called exact matching, compatible matching, sub-expression matching and fuzzy matching. In browser/server mode, 110027 formulae were used as experimental samples. The index file size was 29.02 Mb. The average time of retrieval was 1.092 seconds. The experimental result shows the effectiveness of the method.

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An indexing method of mathematical expression retrieval

Cited by 8 publications

References 7 publications

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

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

A matching model of mathematical expressions with FDS based index

An Improved Indexing and Matching Method for Mathematical Expressions Based on Inter-Relevant Successive Tree

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