Search Augmentation via Social Expert Ranking
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Solution Overview
Problem
Users face the challenge of sifting through vast, often irrelevant search results when seeking information on the internet, making it difficult to obtain manageable amounts of relevant information.
Innovation Solution
A computer system identifies a topic in a query and ranks a set of user friends from social media networks based on their expertise and availability, returning a ranked list of experts for the user to consult.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a user searches for information on the internet using a search engine, then vast amounts of information are returned, but the user must sift through thousands or hundreds of thousands of results containing irrelevant or less relevant information, making it difficult to obtain manageable amounts of relevant information
Solution Approach 1:
The patent extracts and identifies experts from the user's social network who have relevant knowledge about the query topic. Instead of presenting all search results, the system extracts only the most relevant sources of information - namely, connected experts with demonstrated expertise in the query domain. This is achieved by analyzing the expert's profile, publications, and activity to determine their relevance to the user's information need.
2Loss of information
If the user reviews all or a large portion of the search results returned, then more information may be found, but it is infeasible or too time-consuming for the user
Solution Approach 1:
The system performs preliminary identification and ranking of experts before presenting results to the user. By pre-analyzing the expertise levels, availability, and relevance of potential experts in advance, the system prepares a pre-filtered list of the most promising information sources. This preliminary action eliminates the need for users to manually evaluate numerous search results, as the filtering and ranking work has already been completed by the system.
Solution Approach 2:
The system enables users to quickly assess expert availability and expertise levels through self-service features such as availability indicators and expertise profiles. Users can independently determine which experts to contact based on the pre-presented information, eliminating the need for time-consuming manual review of search results while maintaining the ability to make informed decisions about information sources.
3Loss of information
If the user revises the query in an attempt to reduce the number of results and return more relevant results, then more relevant information may be obtained, but in some cases the user is unable to revise the query in a manner that returns a small enough number of results containing relevant information
Solution Approach 1:
The patent introduces an intermediary layer between the user's query and the search results - specifically, the user's social network connections who are identified as experts. Instead of requiring the user to continuously refine their query to filter results, the system uses the intermediary of trusted experts in the user's network to provide pre-filtered, high-quality information. This intermediary approach bypasses the need for complex query revision while maintaining high relevance.
Data Source
AI summary
A method, apparatus, system, and computer program product for processing a query received through a network. A computer system identifies a topic in the query. The computer system identifies a set of friends of a user from a set of social media networks in which the set of the friends have an expertise in the topic identified in the query. The computer system ranks the set of the friends based on a level of the expertise of the set of the friends for the topic and an availability of the set of the friends to form a ranked set of the friends. The computer system returns results that contain the ranked set of the friends for the topic.