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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/27767
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| Title: | Predicting citation rates for physics papers: Constructing features for
an ordered probit model |
| Authors: | Perlich, Claudia
Provost, Foster
Macskassy, Sofus |
| Issue Date: | 1-Jun-2003 |
| Publisher: | SIGKDD |
| Citation: | Volume 5, Issue 2 - Page 154 |
| Series/Report no.: | CeDER-PP-2003-02 |
| Abstract: | Gehrke et al. introduce the citation prediction task in their paper
"Overview of the KDD Cup 2003" (in this issue). The objective
was to predict the <i>change</i>
in the number of citations a paper will receive-not the absolute number
of citations. There are obvious factors affecting the number of
citations including the quality and the topic of the paper, and the
reputation of the authors. However it is not clear which factors might
influence the change in citations between quarters, rendering the
construction of predictive features a challenging task. A high quality
and timely paper will be cited more often than a lower quality paper,
but that does not suggest the change in citation counts. The selection
of training data was critical, as the evaluation would only be on papers
that received more than 5 citations in the quarter following the
submission of results. After considering several modeling approaches, we
used a modified version of an ordered probit model. We describe each of
these steps in turn. |
| URI: | http://hdl.handle.net/2451/27767 |
| Appears in Collections: | CeDER Published Papers
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