Processing Mathematical Notation

Blostein, Dorothea; Zanibbi, Richard

doi:10.1007/978-0-85729-859-1_21

Cited by 5 publications

(3 citation statements)

References 42 publications

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“…The flexibility of mathematical notation benefits both authors and their technical communities. However, this flexibility and dependency on context for interpretation poses substantial challenges for automated recognition and retrieval of mathematical notation [3,37]. 3 m in : a Multimodal Math Search Interface Figure 2 shows the m in search interface which runs in standard web browsers on desktop and tablet computers (e.g.…”

Section: Math Encodings: Symbol Layout Trees and Operator Treesmentioning

confidence: 99%

Section: Math Encodings: Symbol Layout Trees and Operator Treesmentioning

confidence: 99%

“…m in is implemented in Javascript and HTML, with symbol recognition and parsing performed by external web services. 3 In Figure 2 we see a text box for keywords at top-right, while the large white canvas at bottom is used to enter formulae. A list of formula are stored in the 'deck,' the wide rectangular panel at the top of the interface.…”

Section: In : a Multimodal Math Search Interfacementioning

confidence: 99%

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Math Search for the Masses: Multimodal Search Interfaces and Appearance-Based Retrieval

Zanibbi

Orakwue

2015

Lecture Notes in Computer Science

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Abstract. We summarize math search engines and search interfaces produced by the Document and Pattern Recognition Lab in recent years, and in particular the min math search interface and the Tangent search engine. Source code for both systems are publicly available. "The Masses" refers to our emphasis on creating systems for mathematical non-experts, who may be looking to define unfamiliar notation, or browse documents based on the visual appearance of formulae rather than their mathematical semantics.

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Section: Math Encodings: Symbol Layout Trees and Operator Treesmentioning

confidence: 99%

Section: Math Encodings: Symbol Layout Trees and Operator Treesmentioning

confidence: 99%

Section: In : a Multimodal Math Search Interfacementioning

confidence: 99%

See 1 more Smart Citation

Math Search for the Masses: Multimodal Search Interfaces and Appearance-Based Retrieval

Zanibbi

Orakwue

2015

Lecture Notes in Computer Science

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A Hybrid Feature Extraction Method for Offline Handwritten Math Symbol Recognition

Ramírez-Piña

Sánchez

Valdovinos

et al. 2019

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Advancing the state of the art for handwritten math recognition: the CROHME competitions, 2011–2014

Mouchère

Zanibbi

Garain

et al. 2016

IJDAR

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International audienceThe CROHME competitions have helped organize the field of handwritten mathematical expression recognition. This paper presents the evolution of the competition over its first 4 years, and its contributions to handwritten math recognition, and more generally structural pattern recognition research. The competition protocol, evaluation metrics and datasets are presented in detail. Participating systems are analyzed and compared in terms of the central mathematical expression recognition tasks: (1) symbol segmentation, (2) classification of individual symbols, (3) symbol relationships and (4) structural analysis (parsing). The competition led to the development of label graphs, which allow recognition results with conflicting segmentations to be directly compared and quantified using Hamming distances. We introduce structure confusion histograms that provide frequencies for incorrect subgraphs corresponding to ground-truth label subgraphs of a given size and present structure confusion histograms for symbol bigrams (two symbols with a relationship) for CROHME 2014 systems. We provide a novel analysis combining results from competing systems at the level of individual strokes and stroke pairs; this virtual merging of system outputs allows us to more closely examine limitations for current state-of-the-art systems. Datasets along with evaluation and visualization tools produced for the competition are publicly available

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Processing Mathematical Notation

Cited by 5 publications

References 42 publications

Math Search for the Masses: Multimodal Search Interfaces and Appearance-Based Retrieval

Math Search for the Masses: Multimodal Search Interfaces and Appearance-Based Retrieval

A Hybrid Feature Extraction Method for Offline Handwritten Math Symbol Recognition

Advancing the state of the art for handwritten math recognition: the CROHME competitions, 2011–2014

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