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Growing and Nurturing Reading Abilities

IP.com Disclosure Number: IPCOM000247987D
Publication Date: 2016-Oct-14
Document File: 2 page(s) / 33K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a search engine feature that works through web pages, identifies the reading level of the content, and applies the reading level as a filter criterion. By applying the reading proficiency level profile of the user, the system can provide the appropriate content, and then increase the level over time as the user becomes more proficient.

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Growing and Nurturing Reading Abilities

Performing an online search to find the articles that fit a specific reading level, reading purpose, or reading style is a very time-consuming exercise. To identify the quality of the search results, a user still has to open the link from each promising search result and quickly review the contents. This results in the user realizing a lot of unproductive time.

A method is needed to produce search results that match a user's reading abilities for different topics , which could vary greatly across topic domains.

The novel solution is a search engine feature that works through web pages, identifies the reading level of the content, and applies the reading level as a filter criterion. By applying the reading proficiency level profile of the user, the system can provide the appropriate content.

To implement the system for producing search results based on the reading level associated with the content :


1. System detects the reading proficiency of User A per topic over time

A. User A is proficient in computer science and computer engineering

    B. User A is not active in other topics outside of computer-related domains 2. System groups topics into related clusters (e.g., computer science and engineering are close, but criminology and gardening are further away in other topic clusters)

3. User A searches for some information related to computer science


4. System returns scholarly articles matching User A's reading proficiency


5. User A then needs information about plants to order for a garden


6. User A searches for gardening information


7. Because User A's proficiency for garden-related content is not strong, the system filters the results and provides appropriate

options (i.e., returns popular mainstream or hobbyist articles as opposed to e...