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Selectivity Based Tag Enhancement

IP.com Disclosure Number: IPCOM000243592D
Publication Date: 2015-Oct-04
Document File: 2 page(s) / 81K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is an improved method and system for using tags to find content by detecting an intended use of a tag, predicting the selectivity of the tag (by percentage), and automatically suggesting an alternative tag or tag combination.

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Selectivity Based Tag Enhancement

Users tag content so that it is easier to locate in the future. Over time, tags change (e.g., popularity, definition, general usage, etc.) and become less effective for those trying to find the content. For example, a user might have to alter the query plans for a database so that the selectivity of a tag is not the primary factor in selecting content. For users, finding content this way is not only burdensome, but also nearly impossible.

Example of the problem:

1. User A is a member of the Wiki 2. User A tags the Content_A with Tag_Y, but User A does not realize that 40 pieces of content are already tagged with Tag_Y
3. The system adds the Tag_Y to the Content index
4. User B tries to find Content_A using Tag_Y
5. The system returns all the content with Tag_Y

An improved method of tagging/identifying/finding content with tags is needed.

The novel contribution is an improved method and system for using tags to find content by detecting an intended use of a tag, predicting the selectivity of the tag (by percentage), and automatically suggesting an alternative tag or tag combination. The system works with any tag system and can operate using a single entered tag, double tag, triple tag, n-tags, or partial tags.

In a preferred embodiment, the system:

1. Detects the intent for a tag (by intercepting a user interface (UI) operation, detecting a type-ahead on a tag, or preprocessing action when adding a tag)

2. Queries a lookup table containing the frequency of all the tags used in the system

3. Calculates the uniqueness of the tag over the system, and may use other statistical methods to determine uniqueness (e.g., binning, standard deviation, probability)

4. Determines that the uniqueness is over (or...