A survey of visual analytics for knowledge discovery and content analysis

Mohammad S. Habibi; Amir Shirkhodaie

doi:10.1117/12.919311

17 May 2012 A survey of visual analytics for knowledge discovery and content analysis

Proceedings Volume 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI; 83920T (2012) https://doi.org/10.1117/12.919311
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

This survey paper provides a review of tools and concepts of visual analytics, and the challenges faced by researchers developing application for knowledge discovery. A comparison is made based on analytic features, its ability to categorize data, the modeling procedures, visual representation, interoperability, and its reliability and portability. The issues related to heterogeneous data, its scalability and multi-dimensionality is also explored. An efficient, intelligent, interactive and robust visual analytics system allows the discovery of information hidden in a massive and dynamic volume of data, especially in a surveillance system thus creating an effective situation awareness of the environment. While visual analytics is hugely important in knowledge discovery, it is necessary for developers to avoid information overload due to inappropriate, irrelevant and uncertain data due to random or fuzzy sensor inputs, also known as noise. The discovered knowledge is the basis for adaptive situation awareness, as it often provides information beyond the perception of human cognitive mind. The tools and concepts researched for this article includes addressing the human computer interaction aspect for intelligent, adaptive decision making from multiple information resources. An attempt is made in this paper to combine the strengths of smart search and data analysis with visual perception and interactive analysis capability of the user.

Citation Download Citation

Mohammad S. Habibi and Amir Shirkhodaie "A survey of visual analytics for knowledge discovery and content analysis", Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 83920T (17 May 2012); https://doi.org/10.1117/12.919311

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available