A Content Based Mathematical Search Engine: Whelp

Asperti, Andrea; Guidi, Ferruccio; Coen, Claudio Sacerdoti; Tassi, E.; Zacchiroli, Stefano

doi:10.1007/11617990_2

Cited by 35 publications

(26 citation statements)

References 15 publications

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“…Mathematical knowledge management is concerned with the representation, archiving, extraction, and use of mathematical information. Systems for mathematical information retrieval have been developed for a variety of applications: -Supporting proof assistants such as Coq [9] It is interesting to compare question-answering systems to information retrieval systems. For textual data, Salton distinguishes these two types of systems based on the types of data stored and the form queries take [125].…”

Section: Overview Of Mathematical Information Retrievalmentioning

confidence: 99%

“…Recently, question-answering systems for mathematical information have been devised [171]. An example is the well-known Wolfram Alpha web site 9 . The Wolfram Alpha knowledge base includes facts on mathematics and statistics, along with many other topics including the sciences, technology, finance, culture, and geography.…”

Section: Overview Of Mathematical Information Retrievalmentioning

confidence: 99%

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Recognition and retrieval of mathematical expressions

Zanibbi

Blostein

2011

IJDAR

234

112

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Document recognition and retrieval technologies complement one another, providing improved access to increasingly large document collections. While recognition and retrieval of textual information is fairly mature, with wide-spread availability of Optical Character Recognition (OCR) and text-based search engines, recognition and retrieval of graphics such as images, figures, tables, diagrams, and mathematical expressions are in comparatively early stages of research. This paper surveys the state of the art in recognition and retrieval of mathematical expressions, organized around four key problems in math retrieval (query construction, normalization, indexing, and relevance feedback), and four key problems in math recognition (detecting expressions, detecting and classifying symbols, analyzing symbol layout, and constructing a representation of meaning). Of special interest is the machine learning problem of jointly optimizing the component algorithms in a math recognition system, and developing effective indexing, retrieval and relevance feedback algorithms for math retrieval. Another important open problem is developing user interfaces that seamlessly integrate recognition and retrieval. Activity in these important research areas is increasing, in part because math notation provides an excellent domain for studying problems common to many document and graphics recognition and retrieval applications, and also because mature applications will likely provide substantial benefits for education, research, and mathematical literacy.

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Section: Overview Of Mathematical Information Retrievalmentioning

confidence: 99%

Section: Overview Of Mathematical Information Retrievalmentioning

confidence: 99%

Recognition and retrieval of mathematical expressions

Zanibbi

Blostein

2011

IJDAR

234

112

View full text Add to dashboard Cite

show abstract

“…First of all it adds another navigation frame on top which provides a breadcrumb trail and a link to the Whelp search engine. Whelp [3] is a search engine developed in MoWGLI to index and retrieve proofs and definitions in a formal library by means of powerful queries over the mathematical expressions in the statements. As IDA does not have any search or index facilities, this is a pure gain from the formalisation.…”

Section: Documents As Viewsmentioning

confidence: 99%

An Interactive Algebra Course with Formalised Proofs and Definitions

Asperti

Geuvers

Loeb

et al. 2006

Lecture Notes in Computer Science

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Abstract. We describe a case-study of the application of web-technology (Helm [2]) to create web-based didactic material out of a repository of formal mathematics (C-CoRN [5]), using the structure of an existing course (IDA [4]). The paper discusses the difficulties related to associating notation to a formula, the embedding of formal notions into a document (the "view"), and the rendering of proofs.

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“…The topic is particularly relevant for the Mathematical Knowledge Management community since every mathematical assistant sooner or later faces the need of letting its user type formulae. When the user is not acquainted with a system or its library -as it happens when using mathematical search engines [1,3,13] -we cannot assume the knowledge of a language other than the usual corpus of ambiguous mathematical notation.…”

Section: Introductionmentioning

confidence: 99%

Spurious Disambiguation Errors and How to Get Rid of Them

Coen

Zacchiroli

2008

Math.Comput.Sci.

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Abstract. The disambiguation approach to the input of formulae enables users of mathematical assistants to type correct formulae in a terse syntax close to the usual ambiguous mathematical notation. When it comes to incorrect formulae however, far too many typing errors are generated; among them we want to present only errors related to the formula interpretation meant by the user, hiding errors related to other interpretations.We study disambiguation errors and how to classify them into the spurious and genuine error classes. To this end we give a general presentation of the classes of disambiguation algorithms and efficient disambiguation algorithms. We also quantitatively assess the quality of the presented error classification criteria benchmarking them in the setting of a formal development of constructive algebra.

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A Content Based Mathematical Search Engine: Whelp

Cited by 35 publications

References 15 publications

Recognition and retrieval of mathematical expressions

Recognition and retrieval of mathematical expressions

An Interactive Algebra Course with Formalised Proofs and Definitions

Spurious Disambiguation Errors and How to Get Rid of Them

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