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Augmenting Presentation MathML for Search

2008; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-540-85110-3_43

1611-3349

Bruce R. Miller, Abdou Youssef,

Open Education and E-Learning

The ubiquity of text search is both a boon and bane for the quest for math search. A bane in that user's expectations are high regarding accuracy, in-context highlighting and similar features. Yet also a boon with the availability of highly evolved search engine libraries; Youssef has previously shown how an appropriate 'textualization' of mathematics into an indexable form allows standard text search engines to be applied. Furthermore, given sufficiently semantic source forms for the math, such as or Content MathML, the indexed form can be enhanced by co-locating synonyms, aliases and other metadata, thus increasing the accuracy and richness of expression. Unfortunately, Content MathML is not always available, and the conversion from to Presentation MathML (pMML) is too complex to carry out on the fly. Thus, one loses the ability to provide query-specific, fine-grained highlighting within the pMML displayed in search results to the user. Where semantic information is available, however, such as for pMML generated from a richer representation, we propose augmenting the generated pMML with those semantics from which synonyms and other metadata can be reintroduced. Thus, in this paper, we aim to have both the high accuracy introduced by semantics while still obtaining fine-grained highlighting.