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  1. Transactions on Interactive Intelligent Systems (TiiS)
  2. ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 5
  3. Issue 3(Special Issue on Behavior Understanding for Arts and Entertainment (Part 2 of 2) and Regular Articles), October 2015
  4. Exploratory Visual Analysis and Interactive Pattern Extraction from Semi-Structured Data
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ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 7
ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 6
ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 5
Issue 4(Regular Articles and Special issue on New Directions in Eye Gaze for Interactive Intelligent Systems (Part 1 of 2)), January 2016
Issue 3(Special Issue on Behavior Understanding for Arts and Entertainment (Part 2 of 2) and Regular Articles), October 2015
Behavior Understanding for Arts and Entertainment
Interactive Visuals as Metaphors for Dance Movement Qualities
Quantitative Study of Music Listening Behavior in a Smartphone Context
The WOZ Recognizer: A Wizard of Oz Sketch Recognition System
Exploratory Visual Analysis and Interactive Pattern Extraction from Semi-Structured Data
A Review and Taxonomy of Interactive Optimization Methods in Operations Research
Issue 2(Special Issue on Behavior Understanding for Arts and Entertainment (Part 1 of 2)), July 2015
Issue 1, March 2015
ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 4
ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 3
ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 2
ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 1

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Exploratory Visual Analysis and Interactive Pattern Extraction from Semi-Structured Data

Content Provider ACM Digital Library
Author Kešelj, Vlado Soto, Axel J. Milios, Evangelos Kiros, Ryan
Copyright Year 2015
Abstract Semi-structured documents are a common type of data containing free text in natural language (unstructured data) as well as additional information about the document, or meta-data, typically following a schema or controlled vocabulary (structured data). Simultaneous analysis of unstructured and structured data enables the discovery of hidden relationships that cannot be identified from either of these sources when analyzed independently of each other. In this work, we present a visual text analytics tool for semi-structured documents (ViTA-SSD), that aims to support the user in the exploration and finding of insightful patterns in a visual and interactive manner in a semi-structured collection of documents. It achieves this goal by presenting to the user a set of coordinated visualizations that allows the linking of the metadata with interactively generated clusters of documents in such a way that relevant patterns can be easily spotted. The system contains two novel approaches in its back end: a feature-learning method to learn a compact representation of the corpus and a fast-clustering approach that has been redesigned to allow user supervision. These novel contributions make it possible for the user to interact with a large and dynamic document collection and to perform several text analytical tasks more efficiently. Finally, we present two use cases that illustrate the suitability of the system for in-depth interactive exploration of semi-structured document collections, two user studies, and results of several evaluations of our text-mining components.
Starting Page 1
Ending Page 36
Page Count 36
File Format PDF
ISSN 21606455
e-ISSN 21606463
DOI 10.1145/2812115
Volume Number 5
Issue Number 3
Journal ACM Transactions on Interactive Intelligent Systems (TiiS)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-09-08
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Visual text analytics Dimensionality reduction Interactive clustering
Content Type Text
Resource Type Article
Subject Artificial Intelligence Human-Computer Interaction
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