User Search Prioritization via Graph and Indexed Search
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Solution Overview
Problem
Existing communication platforms face inefficiencies in user search features, leading to inaccurate results and high computational loads as the number of users increases, resulting in a poor user experience.
Innovation Solution
Implementing a dual-search approach that combines graph search and indexed search processes to prioritize results based on common connections and relevance, presenting users with a prioritized view of search results that includes annotations indicating the number of shared connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional search features are used to find users in communication platforms, then users can perform basic searches, but the search results become too broad or too narrow and consume excessive processing resources and storage as the number of users increases
Solution Approach 1:
The patent segments the search process into two distinct phases: graph search that leverages social connection networks to identify relevant users, and indexed search that efficiently retrieves user data. This segmentation allows the system to process searches in a distributed manner, reducing the computational burden on any single component and improving overall search efficiency without requiring excessive centralized resources
Solution Approach 2:
The patent introduces common connections as an intermediary layer between the search query and the target user. Instead of directly searching through all users or relying on a single centralized index, the system uses mutual connections as a mediator to narrow down and prioritize search results, reducing the scope of the search and the resources required to process it
2Quantity of substance
If the quantity of users on communication platforms increases, then more users are available for discovery, but searching among the multitude of users consumes more processing resources and storage of pre-searched results
Solution Approach 1:
The patent performs preliminary actions by pre-establishing and maintaining the graph structure of user connections and common relationships in advance. This pre-computed social network data is stored in an optimized format that allows rapid querying, eliminating the need to perform resource-intensive analysis during actual search operations. The system prepares connection maps and mutual relationship data beforehand, so when a search is executed, it can quickly leverage this pre-processed information without consuming excessive real-time processing resources
Solution Approach 2:
The patent implements dynamic search strategies that adapt to the scale of the user base. The graph search component dynamically adjusts the depth and breadth of connection traversal based on the number of users and the specific query, while the indexed search dynamically selects which indexes to query. This dynamic approach ensures that processing resources are optimized regardless of whether the platform has thousands or millions of users
3Ease of operation
If traditional search features are used, then users can search for other users, but the search experience is poor due to difficulty in optimizing search scope
Solution Approach 1:
The patent implements feedback mechanisms that analyze search results and user interactions to continuously optimize search scope. The system monitors which search queries return appropriate results and adjusts the graph search parameters and indexing strategies accordingly. This feedback loop enables the system to learn from actual usage patterns and automatically refine its search scope optimization, improving user experience without requiring manual configuration
Solution Approach 2:
The patent employs parameter changes to optimize search scope based on the specific query and user context. The graph search component dynamically adjusts parameters such as connection depth, relationship weight thresholds, and result ranking criteria based on the query type and user profile. The indexed search similarly adjusts its parameters based on the search terms and expected result set size, allowing the system to optimize search scope for each individual query rather than using fixed parameters
Data Source
AI summary
Systems, apparatuses, services, platforms, and methods are discussed herein that provide user search services to a communication platform. An example user search service receives a query indicted by a user to find users of a communication platform associated with one or more search terms. The example user search service also presents to the user a search result view comprising resultant users on the communication platform, where the search result view includes one or more graphical annotations in association with ones of the resultant users that indicate a quantity of common users on the communication platform between the user and the ones of the resultant users.