Location Context Search System for Relevant Content Filtering
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Solution Overview
Problem
The increasing volume of information on the web makes it challenging for users to find relevant content efficiently, as search engines often return a large number of irrelevant results, requiring users to iteratively modify search queries and sift through numerous sites, ads, and unfiltered data.
Innovation Solution
A location and context-based search system that interacts with a location component to filter web content based on user location and context information, such as user preferences, temporal events, and third-party context, to deliver more relevant results, and a localized marketing service that matches merchant and user settings to provide personalized electronic discount offers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If search engines retrieve and display a large number of websites matching search queries, then the quantity of information available to users increases, but the time and effort required for users to locate relevant information increases significantly
Solution Approach 1:
The system performs preliminary actions by pre-determining user location through GPS or other location services before the search query is fully processed. This location information is then integrated into the search algorithm in advance, filtering and ranking results based on proximity to the user's location before presentation, thereby reducing the time users spend sifting through irrelevant results.
Solution Approach 2:
The search system applies local quality by providing location-specific search results tailored to the user's geographic position. Instead of returning uniform global results, the system modifies the quality and relevance of results based on local context, such as showing nearby businesses, location-specific events, or regionally relevant information first, thereby reducing the time to find relevant information.
2Loss of information
If search engines return comprehensive search results including all matching websites, then the completeness of information is improved, but the complexity of filtering and evaluating results increases
Solution Approach 1:
The system incorporates feedback mechanisms where user interactions with location-based results (such as visits, clicks, or time spent) are fed back into the search algorithm. This feedback continuously refines the location-relevance weighting, improving the system's ability to filter and rank results by location significance without increasing user-facing complexity, thus maintaining information completeness while simplifying filtering.
3Reliability
If search results are filtered and ranked based on multiple criteria including location, then the relevance of results to user needs is improved, but the complexity of the search system increases
Solution Approach 1:
The search system applies segmentation by dividing the ranking process into distinct modules: location determination module, relevance scoring module, and final ranking module. Each module handles a specific aspect of the filtering process independently, making the overall complex system more manageable and maintainable while still achieving high relevance through the combined effect of these segmented functions.
Data Source
AI summary
The subject disclosure pertains to web searches and more particularly toward influencing resultant content to increase relevancy. The resultant content can be influenced by reconfiguring a query and/or filtering results based on user location and/or context information (e.g., user characteristics/profile, prior interaction/usage temporal, current events, and third party state/context . . . ). Furthermore, the disclosure provides for query execution on at least a subset of designated web content, for example as specified by a user. Still further yet, a localized marketing system is disclosed that provides discount offers to users that match merchant criteria including proximity. A system for actively probing populations of users with different parameters and monitoring responses can be employed to collect data for identifying the best discounts and deadlines to offer to users to achieve desired results.