Location-Based Personalized Content Delivery System
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Solution Overview
Problem
Existing location-based content provision systems fail to effectively match user needs as they do not consider the user's current location when recommending content, leading to ineffective personalized content delivery.
Innovation Solution
A method and system that utilize a learning algorithm to determine user preferences based on geographic location, allowing for the provision of location-based personalized content by querying a database with user identification and location data, and displaying links to relevant content on an electronic map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is provided based on user preference alone, then personalization is achieved, but location relevance is lost
Solution Approach 1:
The patent merges user preference data with location data to create a unified recommendation system. The server combines the user preference model (derived from activity data) with the user's current location information to query the database, thereby integrating both personalization and location relevance into a single content delivery mechanism.
Solution Approach 2:
The patent adds a spatial dimension to the content recommendation system. By incorporating location coordinates (latitude and longitude) as an additional dimension alongside user preferences, the system transforms from a one-dimensional preference-based filter to a two-dimensional recommendation model that considers both user taste and geographic context.
2Measurement precision
If location data is integrated into content provision, then location relevance improves, but system complexity increases
Solution Approach 1:
The system automatically obtains location data from the user's device without requiring manual input. The browser program or client device self-provides location information (via GPS, IP address, or other location services) to the server, eliminating the need for complex user interfaces or manual location entry mechanisms.
Solution Approach 2:
The server system is designed to handle multiple functions: it maintains user preference models, processes location data, queries content databases, and delivers personalized recommendations. By consolidating these functions into a single multi-functional server platform, the patent avoids the need for separate specialized systems for each function.
3Quantity of substance
If geographic range is expanded for content search, then content variety increases, but query time increases
Solution Approach 1:
The system pre-establishes user preference models by analyzing historical activity data before actual content queries are needed. This preliminary processing of user behavior patterns allows the server to quickly filter and rank content during real-time queries, reducing the time required to search through large geographic ranges and diverse content databases.
Data Source
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AI summary
A method and a system for providing a location-based personalized content are provided. A serving system (100) is provided for collecting activity data of a user on the Internet and forming location-based personalized data according to geographic information associated with the activity data. Geography-based features related to the activity data can be learned so as to generate a location-based personalized preference model that is used to describe a user preference. When the serving system (100) receives location data from a computer of the user, one or more location-based personalized contents that match the user preference within a geographic range can be obtained. Afterwards, one or more links based on the location-based personalized content is then transmitted to the computer, and the one or more links can be marked in a browsing program executed in the computer.