TY - GEN
T1 - TIARA
T2 - 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD-2010
AU - Wei, Furu
AU - Liu, Shixia
AU - Song, Yangqiu
AU - Pan, Shimei
AU - Zhou, Michelle X.
AU - Qian, Weihong
AU - Shi, Lei
AU - Tan, Li
AU - Zhang, Qiang
PY - 2010
Y1 - 2010
N2 - In this paper, we present a novel exploratory visual analytic system called TIARA (Text Insight via Automated Responsive Analytics), which combines text analytics and interactive visualization to help users explore and analyze large collections of text. Given a collection of documents, TIARA first uses topic analysis techniques to summarize the documents into a set of topics, each of which is represented by a set of keywords. In addition to extracting topics, TIARA derives time-sensitive keywords to depict the content evolution of each topic over time. To help users understand the topic-based summarization results, TIARA employs several interactive text visualization techniques to explain the summarization results and seamlessly link such results to the original text. We have applied TIARA to several real-world applications, including email summarization and patient record analysis. To measure the effectiveness of TIARA, we have conducted several experiments. Our experimental results and initial user feedback suggest that TIARA is effective in aiding users in their exploratory text analytic tasks.
AB - In this paper, we present a novel exploratory visual analytic system called TIARA (Text Insight via Automated Responsive Analytics), which combines text analytics and interactive visualization to help users explore and analyze large collections of text. Given a collection of documents, TIARA first uses topic analysis techniques to summarize the documents into a set of topics, each of which is represented by a set of keywords. In addition to extracting topics, TIARA derives time-sensitive keywords to depict the content evolution of each topic over time. To help users understand the topic-based summarization results, TIARA employs several interactive text visualization techniques to explain the summarization results and seamlessly link such results to the original text. We have applied TIARA to several real-world applications, including email summarization and patient record analysis. To measure the effectiveness of TIARA, we have conducted several experiments. Our experimental results and initial user feedback suggest that TIARA is effective in aiding users in their exploratory text analytic tasks.
KW - Document summarization
KW - Exploratory analytics
KW - Interactive visualization
KW - Topic analysis
KW - Visual text analytics
UR - https://www.scopus.com/pages/publications/77956220483
U2 - 10.1145/1835804.1835827
DO - 10.1145/1835804.1835827
M3 - 会议稿件
AN - SCOPUS:77956220483
SN - 9781450300551
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 153
EP - 162
BT - KDD'10 - Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data
Y2 - 25 July 2010 through 28 July 2010
ER -