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Using semi-structured data for assessing research paper similarity

(2013) INFORMATION SCIENCES. 221(1). p.245-261
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Keywords
Latent Dirichlet Allocation, RETRIEVAL, Language modeling, Document similarity, Semi-structured document

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Citation

Please use this url to cite or link to this publication:

Chicago
Hurtado Martín, Germán, Steven Schockaert, Chris Cornelis, and Helga Naessens. 2013. “Using Semi-structured Data for Assessing Research Paper Similarity.” Information Sciences 221 (1): 245–261.
APA
Hurtado Martín, G., Schockaert, S., Cornelis, C., & Naessens, H. (2013). Using semi-structured data for assessing research paper similarity. INFORMATION SCIENCES, 221(1), 245–261.
Vancouver
1.
Hurtado Martín G, Schockaert S, Cornelis C, Naessens H. Using semi-structured data for assessing research paper similarity. INFORMATION SCIENCES. 2013;221(1):245–61.
MLA
Hurtado Martín, Germán, Steven Schockaert, Chris Cornelis, et al. “Using Semi-structured Data for Assessing Research Paper Similarity.” INFORMATION SCIENCES 221.1 (2013): 245–261. Print.
@article{3220171,
  author       = {Hurtado Mart{\'i}n, Germ{\'a}n and Schockaert, Steven and Cornelis, Chris and Naessens, Helga},
  issn         = {0020-0255},
  journal      = {INFORMATION SCIENCES},
  keyword      = {Latent Dirichlet Allocation,RETRIEVAL,Language modeling,Document similarity,Semi-structured document},
  language     = {eng},
  number       = {1},
  pages        = {245--261},
  title        = {Using semi-structured data for assessing research paper similarity},
  url          = {http://dx.doi.org/10.1016/j.ins.2012.09.044},
  volume       = {221},
  year         = {2013},
}

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