Heterogeneous Networks and Their Applications: Scientometrics, Name Disambiguation, and Topic Modeling

Ben King, Rahul Jha, Dragomir R. Radev


Abstract
We present heterogeneous networks as a way to unify lexical networks with relational data. We build a unified ACL Anthology network, tying together the citation, author collaboration, and term-cooccurence networks with affiliation and venue relations. This representation proves to be convenient and allows problems such as name disambiguation, topic modeling, and the measurement of scientific impact to be easily solved using only this network and off-the-shelf graph algorithms.
Anthology ID:
Q14-1001
Volume:
Transactions of the Association for Computational Linguistics, Volume 2
Month:
Year:
2014
Address:
Cambridge, MA
Editors:
Dekang Lin, Michael Collins, Lillian Lee
Venue:
TACL
SIG:
Publisher:
MIT Press
Note:
Pages:
1–14
Language:
URL:
https://aclanthology.org/Q14-1001
DOI:
10.1162/tacl_a_00161
Bibkey:
Cite (ACL):
Ben King, Rahul Jha, and Dragomir R. Radev. 2014. Heterogeneous Networks and Their Applications: Scientometrics, Name Disambiguation, and Topic Modeling. Transactions of the Association for Computational Linguistics, 2:1–14.
Cite (Informal):
Heterogeneous Networks and Their Applications: Scientometrics, Name Disambiguation, and Topic Modeling (King et al., TACL 2014)
Copy Citation:
PDF:
https://aclanthology.org/Q14-1001.pdf