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Pre-Grant Publication Number: 20080172630

Graphical representation of aggregated data

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Prior Art Detail

Annotations(1)

#270Scalable Visual Analytics of Massive Textual Datasets

Applies to Claims 1,10,14,17,18,2,20,6,9

Submitted by: Yeen ThamLast updated: over 4 years ago

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Summary / Description

Summary / Description	This paper describes the first scalable implementation of a text processing engine used in visual analytics tools.

Basic Information

Type of Prior Art	Print Publication

Publication Title *	Scalable Visual Analytics of Massive Textual Datasets

Author	Krishnan, et al.

ISBN

Page Range	1-10

Medium	Other printed publication

Publication Date *	2007

URL	http://infoviz.pnl.gov/pdf/insp...

Notes / To Do

Notes

Excerpt

Excerpt

This paper describes the first scalable implementation of a text processing engine used in visual analytics tools. These tools aid information analysts in interacting with and understanding large textual information content through visual interfaces. By developing a parallel implementation of the text processing engine, we enabled visual analytics tools to exploit cluster architectures and handle massive datasets. The paper describes key elements of our parallelization approach and demonstrates virtually linear scaling when processing multi-gigabyte data sets such as Pubmed. This approach enables interactive analysis of large datasets beyond capabilities of existing state-of-the art visual analytics tools.

Relevance

Claims

A method for enabling graphical representation of aggregated data comprising:accessing aggregated data retrieved from a plurality of on-line sources;

receiving a selection of a portion of said data through a graphical user interface;

identifying attributes associated with said portion of said data; and

generating a graphical representation of said portion of said data.

Relevance

The article discloses that “current state-of-the-art visual analytics software tools can quickly and automatically convey the gist of large sets of unformatted text documents such as technical reports, web data, newswire feeds and message traffic. Visual analytics software unveils common themes and reveals hidden relationships within document collections. It allows analysts to spend more time exploring the information they find most relevant …”

Claim Chart

All

The method of Claim 1 further comprising:determining a relationship between a first attribute of said portion of said data and a second attribute of said portion of said data; and

generating a graphical representation associated with said relationship.

Relevance

P.2 describes a “visual analytics system designed to enable analysts to rapidly discover information relationships.” This system allows for the structuring of information into “signatures.”

Claim Chart

All

The method of Claim 1 further comprising:accessing a key word associated with said portion of said data; and

generating a graphical representation associated with said keyword.

Relevance

P.3 discloses process stages in the visual analytics system, e.g. step 4 states that the system can use indices to locate “topics” or “major terms”.

Claim Chart

All

Instructions on a computer-usable medium wherein said instructions when executed cause a computer system to perform a method for enabling graphical representation of software security data, said computer-implemented method comprising:accessing aggregated data associated with software vulnerabilities retrieved from a plurality of on-line sources;

receiving a selection of a portion of said data through a graphical user interface;

identifying attributes associated with said portion of said data; and

generating a graphical representation of said portion of said data.

Relevance

Claim Chart

All

The instructions of Claim 9 wherein said method further comprises:determining a relationship between a first attribute of said portion of said data and a second attribute of said portion of said data; and

generating a graphical representation associated with said relationship.

Relevance

P.2 describes a “visual analytics system designed to enable analysts to rapidly discover information relationships.” This system allows for the structuring of information into “signatures.”

Claim Chart

All

The instructions of Claim 9 wherein said method further comprises:accessing a key word associated with said portion of said data; and

generating a graphical representation associated with said keyword.

Relevance

P.3 discloses process stages in the visual analytics system, e.g. step 4 states that the system can use indices to locate “topics” or “major terms”.

Claim Chart

All

A system for enabling graphical representation of software security data comprising:a software security data collector module for accessing data associated with software vulnerabilities from a plurality of on-line sources;

a software security data compiler for aggregating said data from said plurality of on-line sources;

a software security data attribute identifier module for identifying attributes associated with a portion of said data; and

a graphical user interface controller for generating a graphical representation of said portion of said data.

Relevance

Claim Chart

All

The system of Claim 17 further comprising:a data relationship determiner module for determining a relationship between a first attribute of said portion of said data and a second attribute of said portion of said data wherein said graphical user interface generates a graphical representation associated with said relationship.

Relevance

P.2 describes a “visual analytics system designed to enable analysts to rapidly discover information relationships.” This system allows for the structuring of information into “signatures.”

Claim Chart

All

The system of Claim 17 further comprising:a keyword accessor module for accessing a key word associated with said portion of said data wherein said graphical user interface controller generates a graphical representation associated with said keyword.

Relevance

P.3 discloses process stages in the visual analytics system, e.g. step 4 states that the system can use indices to locate “topics” or “major terms”.

Claim Chart

All

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