Location-Based Data Pushing via Nearby User Behavior
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Solution Overview
Problem
Conventional webpage push technologies are limited in predicting user preferences beyond their own behaviors, resulting in a narrow scope of personalized content delivery, which does not effectively anticipate users' potential interests and enhance their experience.
Innovation Solution
A server computer system that receives geolocation data from client devices, identifies nearby devices with similar access patterns, retrieves webpage log data, and customizes content based on the browsing habits of these devices to deliver more relevant and personalized content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If push technology uses user behavior tracking to determine webpage content, then personalized content delivery is achieved, but the scope of predicted interests is limited to existing user behaviors
Solution Approach 1:
The patent introduces nearby users as an intermediary factor to predict target user interests. Instead of relying solely on the target user's own behavior history, the system uses behavior data from nearby users (identified through geolocation) as a mediator to infer potential interests, thereby expanding the prediction scope beyond individual user behaviors
Solution Approach 2:
The patent adds a spatial dimension to user behavior analysis by incorporating geolocation data. This transforms the traditional one-dimensional user behavior tracking into a multi-dimensional approach that considers both user behavior patterns and geographical proximity, enabling prediction of interests based on location-based context and nearby user activities
2Ease of operation
If push technology relies on individual user behavior data, then content personalization is achieved, but user experience enhancement is limited
Solution Approach 1:
The patent merges multiple data sources including the target user's behavior data, nearby user behavior data, and geolocation information to create a comprehensive content recommendation system. This combination of data dimensions enriches the content scope while maintaining personalization, thereby enhancing user experience through more versatile and accurate content delivery
Data Source
AI summary
In accordance with a method for location based data pushing, a computer server receives first geolocation data that identify a first geolocation of a first client device, and identifies a plurality of second client devices as located within a predetermined range of the first geolocation. In response to the identifying, the computer server retrieves webpage log data that record information concerning a plurality of websites that have been accessed by the second client devices. Further, in response to a web access request received from the first client device for accessing a webpage, the computer server identifies, among the retrieved webpage log data, one or more web pages as being related to the webpage associated with the web access request, and transmits information of at least one identified webpage and the webpage associated with the web access request to the first client device.


