268 0

SimCC-AT: A Method to Compute Similarity of Scientific Papers with Automatic Parameter Tuning

Title
SimCC-AT: A Method to Compute Similarity of Scientific Papers with Automatic Parameter Tuning
Author
김상욱
Keywords
Automatic weighting; Citations; Content; Contribution score; Similarity
Issue Date
2016-07
Publisher
ACM SIGIR2016
Citation
SIGIR 2016 - Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, Page. 1005-1008
Abstract
In this paper, we propose SimCC-AT (similarity based on content and citations with automatic parameter tuning) to compute the similarity of scientific papers. As in SimCC, the state-of-the-art method, we exploit a notion of a contribution score in similarity computation. SimCC-AT utilizes an automatic weighting scheme based on SVMrank and thus requires only a smaller number of experiments for parameter tuning than SimCC. Furthermore, our experimental results with a real-world dataset show that the accuracy of SimCC-AT is dramatically higher than that of other existing methods and is comparable to that of SimCC.
URI
https://dl.acm.org/citation.cfm?doid=2911451.2914715https://repository.hanyang.ac.kr/handle/20.500.11754/74364
ISBN
978-1-4503-4069-4
DOI
10.1145/2911451.2914715
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE