Wikifying Novel Words to Mixtures of Wikipedia Senses by Structured Sparse Coding
Authors | The wikipage input value is empty (e.g. [[]], [[]] ) and therefore it cannot be used as a name or as part of a query condition. |
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Publication date | 2015 |
DOI | 10.1007/978-3-319-12610-4_15 |
Links | Original Preprint |
Wikifying Novel Words to Mixtures of Wikipedia Senses by Structured Sparse Coding - scientific work related to Wikipedia quality published in 2015, written by [[]].
Overview
Authors extend the scope of Wikification to novel words by relaxing two premises of Wikification: (i) authors wikify without using the surface form of the word (ii) to a mixture of Wikipedia senses instead of a single sense. Authors identify two types of “novel” words: words where the connection between their surface form and their meaning is broken (e.g., a misspelled word), and words where there is no meaning to connect to—the meaning itself is also novel. Authors propose a method capable of wikifying both types of novel words while also dealing with the inherently large-scale disambiguation problem. Authors show that the method can disambiguate between up to 1,000 Wikipedia senses, and it can explain words with novel meaning as a mixture of other, possibly related senses. This mixture representation compares favorably to the widely used bag of words representation.
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Wikipedia Quality
. (2015). "[[Wikifying Novel Words to Mixtures of Wikipedia Senses by Structured Sparse Coding]]". Springer, Cham. DOI: 10.1007/978-3-319-12610-4_15.
English Wikipedia
{{cite journal |last1= |title=Wikifying Novel Words to Mixtures of Wikipedia Senses by Structured Sparse Coding |date=2015 |doi=10.1007/978-3-319-12610-4_15 |url=https://wikipediaquality.com/wiki/Wikifying_Novel_Words_to_Mixtures_of_Wikipedia_Senses_by_Structured_Sparse_Coding |journal=Springer, Cham}}
HTML
. (2015). "<a href="https://wikipediaquality.com/wiki/Wikifying_Novel_Words_to_Mixtures_of_Wikipedia_Senses_by_Structured_Sparse_Coding">Wikifying Novel Words to Mixtures of Wikipedia Senses by Structured Sparse Coding</a>". Springer, Cham. DOI: 10.1007/978-3-319-12610-4_15.