@inproceedings{e2fbe21e4cbf4bd283f99b6a77e40414,
title = "CSSeer: An expert recommendation system based on CiteseerX",
abstract = "We propose CSSeer1, a free and publicly available keyphrase based recommendation system for expert discovery based on the CiteSeerX digital library and Wikipedia as an auxiliary resource. CSSeer generates keyphrases from the title and the abstract of each document in CiteSeerX. These keyphrases are then utilized to infer the authors' expertise. We compared CSSeer with the other two state-of-the-art expert recommenders and found that the three systems have moderately divergent recommendations on 20 benchmark queries. Thus, we recommend users to browse through several different recommenders to obtain a more complete expert list.",
keywords = "Citeseerx, Csseer, Expert recommendation, Information extraction, Keyphrase extraction, Text mining",
author = "Chen, {Hung Hsuan} and Pucktada Treeratpituk and Prasenjit Mitra and {Lee Giles}, C.",
year = "2013",
doi = "10.1145/2467696.2467750",
language = "???core.languages.en_GB???",
isbn = "9781450320764",
series = "Proceedings of the ACM/IEEE Joint Conference on Digital Libraries",
pages = "381--382",
booktitle = "JCDL 2013 - Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries",
note = "13th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2013 ; Conference date: 22-07-2013 Through 26-07-2013",
}