18106715. CLUSTERED METASEARCH simplified abstract (Insight Direct USA, Inc.)

CLUSTERED METASEARCH

Organization Name

Insight Direct USA, Inc.

Inventor(s)

Cathy Snell of Durham NC (US)

Dhairya Kothari of Chicago IL (US)

CLUSTERED METASEARCH - A simplified explanation of the abstract

This abstract first appeared for US patent application 18106715 titled 'CLUSTERED METASEARCH

Simplified Explanation

A clustered metasearch system utilizes Natural Language Processing to improve search results

• The system identifies the object and descriptors of a search query using Natural Language Processing.
• Searches are sorted into relevant realms based on the object of the query.
• The system conducts searches across multiple search engines and collects root domains from the results.
• Root domains within the same realm as the search query are prioritized.
• Additional factors such as the presence of descriptors, recency of the result, search engine rank, and distance from the center of the realm are used to determine final ranking.

Potential Applications

This technology could be applied in various industries such as e-commerce, research, and information retrieval systems.

Problems Solved

This technology helps improve the accuracy and relevance of search results, saving users time and effort in finding the information they need.

Benefits

Users can expect more precise and relevant search results, leading to a better overall search experience.

Potential Commercial Applications

"Enhancing Search Results with Clustered Metasearch System Technology"

Possible Prior Art

There may be prior art related to metasearch systems and Natural Language Processing techniques used in search engines.

Unanswered Questions

1. How does the system handle privacy and data security concerns when collecting search results from multiple search engines? 2. What measures are in place to ensure the accuracy and reliability of the search results provided to users?

Original Abstract Submitted

A clustered metasearch system receives a search query from a user. The system uses Natural Language Processing to identify an object of the search query and descriptors of the search query. The system sorts the search into an applicable realm based on the object of the search query. The system then conducts the search across a variety of search engines and collects root domains from the search results. Root domains within the same realm as the search query are prioritized and additional factors such as the presence of descriptors in the result, the recency of the result, the search engine rank of the result, and the distance from the center of the realm are used to determine the final ranking of the results. The results are then displayed to a user.