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ACM Transactions on Intelligent Systems and Technology (TIST), Volume 3 Issue 2, February 2012

Introduction to the Special Section on Intelligent Visual Interfaces for Text Analysis
Shixia Liu, Michelle X. Zhou, Giuseppe Carenini, Huamin Qu
Article No.: 19
DOI: 10.1145/2089094.2089095

Watch the Story Unfold with TextWheel: Visualization of Large-Scale News Streams
Weiwei Cui, Huamin Qu, Hong Zhou, Wenbin Zhang, Steve Skiena
Article No.: 20
DOI: 10.1145/2089094.2089096

Keyword-based searching and clustering of news articles have been widely used for news analysis. However, news articles usually have other attributes such as source, author, date and time, length, and sentiment which should be taken into account....

Visual Abstraction and Ordering in Faceted Browsing of Text Collections
Vinhtuan Thai, Pierre-Yves Rouille, Siegfried Handschuh
Article No.: 21
DOI: 10.1145/2089094.2089097

Faceted navigation is a technique for the exploration and discovery of a collection of resources, which can be of various types including text documents. While being information-rich resources, documents are usually not treated as content-bearing...

PhC: Multiresolution Visualization and Exploration of Text Corpora with Parallel Hierarchical Coordinates
K. Selçuk Candan, Luigi Di Caro, Maria Luisa Sapino
Article No.: 22
DOI: 10.1145/2089094.2089098

The high-dimensional nature of the textual data complicates the design of visualization tools to support exploration of large document corpora. In this article, we first argue that the Parallel Coordinates (PC) technique, which can map...

TopicNets: Visual Analysis of Large Text Corpora with Topic Modeling
Brynjar Gretarsson, John O’Donovan, Svetlin Bostandjiev, Tobias Höllerer, Arthur Asuncion, David Newman, Padhraic Smyth
Article No.: 23
DOI: 10.1145/2089094.2089099

We present TopicNets, a Web-based system for visual and interactive analysis of large sets of documents using statistical topic models. A range of visualization types and control mechanisms to support knowledge discovery are presented....

DClusterE: A Framework for Evaluating and Understanding Document Clustering Using Visualization
Yi Zhang, Tao Li
Article No.: 24
DOI: 10.1145/2089094.2089100

Over the last decade, document clustering, as one of the key tasks in information organization and navigation, has been widely studied. Many algorithms have been developed for addressing various challenges in document clustering and for improving...

TIARA: Interactive, Topic-Based Visual Text Summarization and Analysis
Shixia Liu, Michelle X. Zhou, Shimei Pan, Yangqiu Song, Weihong Qian, Weijia Cai, Xiaoxiao Lian
Article No.: 25
DOI: 10.1145/2089094.2089101

We are building an interactive visual text analysis tool that aids users in analyzing large collections of text. Unlike existing work in visual text analytics, which focuses either on developing sophisticated text analytic techniques or inventing...

Feature-Based Visual Sentiment Analysis of Text Document Streams
Christian Rohrdantz, Ming C. Hao, Umeshwar Dayal, Lars-Erik Haug, Daniel A. Keim
Article No.: 26
DOI: 10.1145/2089094.2089102

This article describes automatic methods and interactive visualizations that are tightly coupled with the goal to enable users to detect interesting portions of text document streams. In this scenario the interestingness is derived from the...

Introduction to the Special Section on the 2nd Asia Conference on Machine Learning (ACML 2010)
Masashi Sugiyama, Qiang Yang
Article No.: 27
DOI: 10.1145/2089094.2089103

Conceptual Imitation Learning in a Human-Robot Interaction Paradigm
Hossein Hajimirsadeghi, Majid Nili Ahmadabadi, Babak Nadjar Araabi, Hadi Moradi
Article No.: 28
DOI: 10.1145/2089094.2089104

In general, imitation is imprecisely used to address different levels of social learning from high-level knowledge transfer to low-level regeneration of motor commands. However, true imitation is based on abstraction and conceptualization. This...

Mining Recurring Concept Drifts with Limited Labeled Streaming Data
Peipei Li, Xindong Wu, Xuegang Hu
Article No.: 29
DOI: 10.1145/2089094.2089105

Tracking recurring concept drifts is a significant issue for machine learning and data mining that frequently appears in real-world stream classification problems. It is a challenge for many streaming classification algorithms to learn recurring...

Ensembles of Restricted Hoeffding Trees
Albert Bifet, Eibe Frank, Geoff Holmes, Bernhard Pfahringer
Article No.: 30
DOI: 10.1145/2089094.2089106

The success of simple methods for classification shows that is is often not necessary to model complex attribute interactions to obtain good classification accuracy on practical problems. In this article, we propose to exploit this phenomenon in...

A Reliable People Counting System via Multiple Cameras
Huadong Ma, Chengbin Zeng, Charles X. Ling
Article No.: 31
DOI: 10.1145/2089094.2089107

Reliable and real-time people counting is crucial in many applications. Most previous works can only count moving people from a single camera, which cannot count still people or can fail badly when there is a crowd (i.e., heavy occlusion occurs)....

A Fuzzy Logic System for Bargaining in Information Markets
Kostas Kolomvatsos, Christos Anagnostopoulos, Stathes Hadjiefthymiades
Article No.: 32
DOI: 10.1145/2089094.2089108

Future Web business models involve virtual environments where entities interact in order to sell or buy information goods. Such environments are known as Information Markets (IMs). Intelligent agents are used in IMs for representing buyers or...

Batch Mode Active Learning for Networked Data
Lixin Shi, Yuhang Zhao, Jie Tang
Article No.: 33
DOI: 10.1145/2089094.2089109

We study a novel problem of batch mode active learning for networked data. In this problem, data instances are connected with links and their labels are correlated with each other, and the goal of batch mode active learning is to exploit the...

Adversarial Geospatial Abduction Problems
Paulo Shakarian, John P. Dickerson, V. S. Subrahmanian
Article No.: 34
DOI: 10.1145/2089094.2089110

Geospatial Abduction Problems (GAPs) involve the inference of a set of locations that “best explain” a given set of locations of observations. For example, the observations might include locations where a serial killer committed...

Learning to Infer the Status of Heavy-Duty Sensors for Energy-Efficient Context-Sensing
Xueying Li, Huanhuan Cao, Enhong Chen, Jilei Tian
Article No.: 35
DOI: 10.1145/2089094.2089111

With the prevalence of smart mobile devices with multiple sensors, the commercial application of intelligent context-aware services becomes more and more attractive. However, limited by the battery capacity, the energy efficiency of...

Advertising Keywords Recommendation for Short-Text Web Pages Using Wikipedia
Weinan Zhang, Dingquan Wang, Gui-Rong Xue, Hongyuan Zha
Article No.: 36
DOI: 10.1145/2089094.2089112

Advertising keywords recommendation is an indispensable component for online advertising with the keywords selected from the target Web pages used for contextual advertising or sponsored search. Several ranking-based algorithms have been proposed...

Leveraging Auxiliary Data for Learning to Rank
Ke Zhou, Jing Bai, Hongyuan Zha, Gui-Rong Xue
Article No.: 37
DOI: 10.1145/2089094.2089113

In learning to rank, both the quality and quantity of the training data have significant impacts on the performance of the learned ranking functions. However, in many applications, there are usually not sufficient labeled training data for the...

Mining the “Voice of the Customer” for Business Prioritization
Wei Peng, Tong Sun, Shriram Revankar, Tao Li
Article No.: 38
DOI: 10.1145/2089094.2089114

To gain competitiveness and sustained growth in the 21st century, most businesses are on a mission to become more customer-centric. In order to succeed in this endeavor, it is crucial not only to synthesize and analyze the VOC (the...