Network Service Recommendation via Browsing Sequence Mapping
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Solution Overview
Problem
Current network service recommendation strategies, such as association rules and collaborative filtering, assume a uniform interest among all users, leading to inaccurate recommendations that do not satisfy individual user interests, resulting in a low accuracy rate of recommended services.
Innovation Solution
A method and apparatus that acquire historical browsing records, establish browsing sequences, map them to mapping values, aggregate users into groups based on these values, and recommend services tailored to each user's group, improving the accuracy of service recommendations by aligning with individual user interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network services are recommended based on the interest of an entire user group, then the recommendation system can be simple and fast, but the accuracy of matching individual user interests deteriorates
Solution Approach 1:
The patent segments the entire user group into multiple user groups based on browsing behavior sequences. Each user is assigned to a specific group according to their browsing pattern similarity, allowing recommendations to be tailored to each segment rather than treating all users uniformly. This resolves the contradiction by enabling personalized recommendations without requiring complex individual analysis of each user.
Solution Approach 2:
The patent transforms the recommendation approach by changing the parameter from individual user analysis to group-based analysis. By mapping browsing sequences to mapping values and aggregating users into groups based on these values, the system achieves a balance between computational simplicity and recommendation accuracy, resolving the trade-off between speed and precision.
2Measurement precision
If network services are recommended based on individual user interests, then recommendation accuracy improves, but system complexity increases
Solution Approach 1:
The patent reduces system complexity by segmenting users into groups rather than analyzing each user individually. The segmentation is achieved through mapping browsing sequences to mapping values and aggregating users with similar values into the same group. This approach maintains high recommendation accuracy while significantly reducing the computational complexity compared to individual user analysis.
Solution Approach 2:
The patent creates simplified representations (mapping values) of complex browsing sequences. Instead of processing the entire browsing history of each user, the system generates compact mapping values that capture essential browsing patterns. This copying approach preserves the information needed for accurate recommendations while reducing system complexity.
Data Source
AI summary
The present disclosure relates to network data analysis technology, and discloses a method and an apparatus for recommending a network service. The method includes: acquiring a historical browsing record of each user account on a network service; establishing a browsing sequence of each user account according to the historical browsing record corresponding to each user account; mapping the browsing sequence of each user account to a mapping value; aggregating all user accounts according to the mapping value corresponding to each user account, to obtain at least one user account group; and recommending the network service to each user account based on a user account group to which the user account belongs. The present disclosure improves an accuracy rate of whether a recommended network service satisfies an interest of a user in the network service.