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An exploratory study on content-based filtering of call for papers

Germán Hurtado Martín, Steven Schockaert UGent, Chris Cornelis UGent and Helga Naessens UGent (2013) Lecture Notes in Computer Science. 8201. p.58-69
abstract
Due to the increasing number of conferences, researchers need to spend more and more time browsing through the respective calls for papers (CFPs) to identify those conferences which might be of interest to them. In this paper we study several content-based techniques to filter CFPs retrieved from the web. To this end, we explore how to exploit the information available in a typical CFP: a short introductory text, topics in the scope of the conference, and the names of the people in the program committee. While the introductory text and the topics can be directly used to model the document (e.g. to derive a tf-idf weighted vector), the names of the members of the program committee can be used in several indirect ways. One strategy we pursue in particular is to take into account the papers that these people have recently written. Along similar lines, to find out the research interests of the users, and thus to decide which CFPs to select, we look at the abstracts of the papers that they have recently written. We compare and contrast a number of approaches based on the vector space model and on generative language models.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
Information retrieval, Vector space model, Recommendation, Language models, Call for papers
in
Lecture Notes in Computer Science
Lect. Notes Comput. Sci.
editor
Mihai Lupu, Evangelos Kanoulas and Fernando Loizides
volume
8201
issue title
Multidisciplinary information retrieval
pages
58 - 69
publisher
Springer
place of publication
Berlin, Germany
conference name
6th Information Retrieval Facility Conference (IRFC 2013)
conference location
Limassol, Cyprus
conference start
2013-10-07
conference end
2013-10-09
ISSN
0302-9743
ISBN
9783642410574
9783642410567
DOI
10.1007/978-3-642-41057-4_7
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
4160890
handle
http://hdl.handle.net/1854/LU-4160890
date created
2013-10-11 13:59:34
date last changed
2017-01-02 09:52:44
@inproceedings{4160890,
  abstract     = {Due to the increasing number of conferences, researchers need to spend more and more time browsing through the respective calls for papers (CFPs) to identify those conferences which might be of interest to them. In this paper we study several content-based techniques to filter CFPs retrieved from the web. To this end, we explore how to exploit the information available in a typical CFP: a short introductory text, topics in the scope of the conference, and the names of the people in  the program committee. While the introductory text and the topics can be directly used to model the document (e.g. to derive a tf-idf weighted vector), the names of the members of the program committee can be used in several indirect ways. One strategy we pursue in particular is to take into account the papers that these people have recently written. Along similar lines, to find out the research interests of the users, and thus  to decide which CFPs to select, we look at the abstracts of the papers that they have recently written. We compare and contrast a number of approaches based on the vector space model and on generative language models.},
  author       = {Hurtado Mart{\'i}n, Germ{\'a}n and Schockaert, Steven and Cornelis, Chris and Naessens, Helga},
  booktitle    = {Lecture Notes in Computer Science},
  editor       = {Lupu, Mihai and Kanoulas, Evangelos and Loizides, Fernando},
  isbn         = {9783642410574},
  issn         = {0302-9743},
  keyword      = {Information retrieval,Vector space model,Recommendation,Language models,Call for papers},
  language     = {eng},
  location     = {Limassol, Cyprus},
  pages        = {58--69},
  publisher    = {Springer},
  title        = {An exploratory study on content-based filtering of call for papers},
  url          = {http://dx.doi.org/10.1007/978-3-642-41057-4\_7},
  volume       = {8201},
  year         = {2013},
}

Chicago
Hurtado Martín, Germán, Steven Schockaert, Chris Cornelis, and Helga Naessens. 2013. “An Exploratory Study on Content-based Filtering of Call for Papers.” In Lecture Notes in Computer Science, ed. Mihai Lupu, Evangelos Kanoulas, and Fernando Loizides, 8201:58–69. Berlin, Germany: Springer.
APA
Hurtado Martín, G., Schockaert, S., Cornelis, C., & Naessens, H. (2013). An exploratory study on content-based filtering of call for papers. In M. Lupu, E. Kanoulas, & F. Loizides (Eds.), Lecture Notes in Computer Science (Vol. 8201, pp. 58–69). Presented at the 6th Information Retrieval Facility Conference (IRFC 2013), Berlin, Germany: Springer.
Vancouver
1.
Hurtado Martín G, Schockaert S, Cornelis C, Naessens H. An exploratory study on content-based filtering of call for papers. In: Lupu M, Kanoulas E, Loizides F, editors. Lecture Notes in Computer Science. Berlin, Germany: Springer; 2013. p. 58–69.
MLA
Hurtado Martín, Germán, Steven Schockaert, Chris Cornelis, et al. “An Exploratory Study on Content-based Filtering of Call for Papers.” Lecture Notes in Computer Science. Ed. Mihai Lupu, Evangelos Kanoulas, & Fernando Loizides. Vol. 8201. Berlin, Germany: Springer, 2013. 58–69. Print.