TY - GEN
T1 - Keyword extraction for social snippets
AU - Li, Zhenhui
AU - Zhou, Ding
AU - Juan, Yun Fang
AU - Han, Jiawei
PY - 2010
Y1 - 2010
N2 - Today, a huge amount of text is being generated for social purposes on social networking services on the Web. Unlike traditional documents, such text is usually extremely short and tends to be informal. Analysis of such text benefit many applications such as advertising, search, and content filtering. In this work, we study one traditional text mining task on such new form of text, that is extraction of meaningful keywords. We propose several intuitive yet useful features and experiment with various classification models. Evaluation is conducted on Facebook data. Performances of various features and models are reported and compared.
AB - Today, a huge amount of text is being generated for social purposes on social networking services on the Web. Unlike traditional documents, such text is usually extremely short and tends to be informal. Analysis of such text benefit many applications such as advertising, search, and content filtering. In this work, we study one traditional text mining task on such new form of text, that is extraction of meaningful keywords. We propose several intuitive yet useful features and experiment with various classification models. Evaluation is conducted on Facebook data. Performances of various features and models are reported and compared.
UR - http://www.scopus.com/inward/record.url?scp=77954601926&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954601926&partnerID=8YFLogxK
U2 - 10.1145/1772690.1772845
DO - 10.1145/1772690.1772845
M3 - Conference contribution
AN - SCOPUS:77954601926
SN - 9781605587998
T3 - Proceedings of the 19th International Conference on World Wide Web, WWW '10
SP - 1143
EP - 1144
BT - Proceedings of the 19th International Conference on World Wide Web, WWW '10
T2 - 19th International World Wide Web Conference, WWW2010
Y2 - 26 April 2010 through 30 April 2010
ER -