Presenters are listed in italic.
Introduction
8:50-9:00am
Keynote
9:00-10:000am
Michael W. Berry, University of Tennessee, Knoxville
“Tapping Social Media for Sentiments with Live Customer Intelligence (LCI)”
Malu Castellanos, Hewlett-Packard Laboratories
Abstract :
The explosion of Web opinion data that Web 2.0 and its increasingly popular social sites like Twitter,
Facebook, blogs and review sites have brought about, has made essential the need for automatic tools to analyze and understand sentiments toward different topics. This has fueled the emerging field known as sentiment analysis whose goal is to translate the vagaries of human emotion into hard data. Live
Customer Intelligence (LCI) is a system that taps into what is being said to understand the sentiment with the particular ability of doing so in near real-time. LCI integrates novel algorithms for sentiment analysis and a configurable dashboard with different kinds of charts including dynamic ones that change as new data is ingested. LCI has been researched and prototyped at HP Labs in close interaction with business divisions and a few selected customers. In this talk I give an overview of LCI, focusing in particular on challenging issues and illustrating its capabilities with selected use cases.
10:00-10:30am Coffee Break
Session I:
10:30-11:00am
Document Ranking and Representation (Michael W. Berry, Chair)
“Finding Interesting Documents in a Corpus”
Pradeep Chandrasekaran and David Skillicorn
11:00-11:30am “Latent Semantic Indexing with Selective Query Expansion”
Andy Garron and April Kontostathis
11:30am-1:00pm Lunch
Session II: Document Classification, Clustering, and Summarization (Jacob Kogan,
Chair)
1:00-1:30pm “Incremental Clustering of News Reports”
Joel Azzopardi and Christopher Staff
1:30-2:00pm
“The Effects of Tabular-based Content Extraction on Patent
Document Clustering”
Denise Koessler , Benjamin Martin, and Bruce Kiefer, and Michael W. Berry
2:00-2:30pm “Extracting Hierarchies from Data Clusters for Better Classification”
German Sapozhnikov and Alexander Ulanov
2:30-3:00pm
“Better Metrics to Automatically Predict the Quality of a Text Summary”
Peter Rankel , John Conroy and Judith Schlesinger

3:00-3:30pm Coffee Break
Session III: Anomaly Detection (Jacob Kogan, Chair)
3:30-4:00pm
“Contextual Anomaly Detection In Text Data”
Amogh Mahapatra , Nisheeth Srivastava and Jaideep Srivastava
4:00pm Adjourn