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Domain-Specific Semantic Relatedness from Wikipedia Structure: A Case Study in Biomedical Text

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Domain-Specific Semantic Relatedness from Wikipedia Structure: A Case Study in Biomedical Text (English)

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2

Evangelos E. Milios

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P.D. Kadam

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Kadam PD

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H.H. Chuan

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2

object named as

Chuan HH

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Vlado Keselj

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Vlado Kešelj

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Jeannette C. M. Janssen

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language of work or name

English

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publication date

2015

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published in

Computational Linguistics and Intelligent Text Processing: 16th International Conference, CICLing 2015, Cairo, Egypt, April 14-20, 2015, Proceedings, Part I

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volume

27

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issue

3

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page(s)

347-360

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cites work

Computing semantic relatedness using Wikipedia-based explicit semantic analysis

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The Google Similarity Distance

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https://api.crossref.org/works/10.1007%2F978-3-319-18111-0_26

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31 March 2020

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https://api.crossref.org/works/10.1007%2F978-3-319-18111-0_26

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31 March 2020

Citation analysis: A social and dynamic approach to knowledge organization

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https://api.crossref.org/works/10.1007%2F978-3-319-18111-0_26

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31 March 2020

Authoritative sources in a hyperlinked environment

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https://api.crossref.org/works/10.1007%2F978-3-319-18111-0_26

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31 March 2020

Contextual correlates of semantic similarity

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https://api.crossref.org/works/10.1007%2F978-3-319-18111-0_26

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31 March 2020

Towards a framework for developing semantic relatedness reference standards

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https://api.crossref.org/works/10.1007%2F978-3-319-18111-0_26

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31 March 2020

Measures of semantic similarity and relatedness in the biomedical domain

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https://api.crossref.org/works/10.1007%2F978-3-319-18111-0_26

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31 March 2020

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reference URL

https://api.crossref.org/works/10.1007%2F978-3-319-18111-0_26

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31 March 2020

Toward using confidence intervals to compare correlations.

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https://api.crossref.org/works/10.1007%2F978-3-319-18111-0_26

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31 March 2020

Identifiers

DOI

10.1007/978-3-319-18111-0_26

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DBLP publication ID

conf/cicling/SajadiMKJ15

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DBLP Dataset 2021-01-02

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28 January 2021

(Q28042784)

Domain-Specific Semantic Relatedness from Wikipedia Structure: A Case Study in Biomedical Text

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