Browse Prior Art Database

Colorized Contextual Tag Clouds

IP.com Disclosure Number: IPCOM000233915D
Publication Date: 2013-Dec-30
Document File: 2 page(s) / 86K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed are a system and method to provide additional contextual information to traditional tag clouds by colorizing the content.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 52% of the total text.

Page 01 of 2

Colorized Contextual Tag Clouds

Tag clouds are an amazing visualization tool that helps readers understand the frequency by which a given word or phrase is used based on the size of the word. The current state of the tag cloud approach lacks additional contextual information that provides meaning as to why the frequency might be so high. For example, suppose a tag cloud were to show the most frequently used team names for major league baseball. The user has no way of knowing why Team X is showing so much larger than the other teams. The reason could be anything from a big win to a scandal about a player.

Disclosed are a system and method to provide additional contextual information to traditional tag clouds by colorizing the content.

The components and process for implementing the system and method in a preferred embodiment follow:

1. Per current processes, user searches for a term or phrase or otherwise gets to a location in which a tag cloud is shown


2. Along with each term and its frequency, additional information is determined

A. Tags associated with the terms

B. User votes on like or dislike (this could be determined using known technologies such as social networking analysis)

C. Surrounded words (e.g., Team X won assumes the team won; Team Z lost assumes the team lost; Team X 5-4 win over Team Z assumes Team

X won, Team Z lost)


3. The sentiment is gathered from Step 2 and assumed with the term


4. Sentiment can be optionally limited by a time range (e.g., last hour, last day, last

week, last year, etc.)

5. Based on the percentage of the sentiment strength, the term is colorized (e.g., 75% negative, color orange; 90% positive, color green)


6. When the user hovers over the term, the system presents the justifica...