Integration of opinion mining service flow with anonymous information

Authors:
Iee Joon Kim;Jae Yoel Yoon;Ji Yeon Lim;Seung Kwan Kim;Ung Mo Kim
Affiliations:
SungKyunKwan University, CheonCheon-Dong, JangAn-Gu, Suwon, Gyueongi-do, South Korea;SungKyunKwan University, CheonCheon-Dong, JangAn-Gu, Suwon, Gyueongi-do, South Korea;SungKyunKwan University, CheonCheon-Dong, JangAn-Gu, Suwon, Gyueongi-do, South Korea;SungKyunKwan University, CheonCheon-Dong, JangAn-Gu, Suwon, Gyueongi-do, South Korea;SungKyunKwan University, CheonCheon-Dong, JangAn-Gu, Suwon, Gyueongi-do, South Korea
Venue:
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Year:
2012

Citing 5
Cited 0

Mining and summarizing customer reviews

Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Determining the sentiment of opinions

COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Opinion spam and analysis

WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Opinion Mining and Sentiment Analysis

Foundations and Trends in Information Retrieval
Extracting opinions, opinion holders, and topics expressed in online news media text

SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text

Quantified Score

Hi-index	0.00

Visualization

Abstract

Nowadays, we are exposed to lots of digital data. You cannot imagine how many data is creating even now in the world. However, we cannot know and find which and where is the data really what we needed. Moreover, we cannot trust whether someone is telling the truth or not on the web. So, our study is giving you the service flow how to choose data wisely. And, in our study, we include anonymous information for increasing data correction.