Vector Mapping Modules for User Interest Estimation
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Solution Overview
Problem
Existing methods for estimating user interests struggle due to the difficulty in comparing and analyzing user events from different types, as they are conventionally represented using different information formats, leading to inefficient analysis.
Innovation Solution
The method involves mapping user events to vectors in multidimensional spaces, allowing for the analysis of these vectors to determine messages of interest to users, using vector-mapping modules that transform input vectors into output vectors in various multidimensional spaces, enabling the comparison and aggregation of disparate user event types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If different types of user events are stored in different information formats, then each type of information can be represented in a format suitable for representing that type, but the user events become difficult to compare and analyze
Solution Approach 1:
The patent applies universality by creating a unified vector representation format that can accommodate multiple types of user events (clicks, views, purchases, etc.) that were previously stored in different formats. The vector mapping modules transform diverse event types into a common multidimensional vector space, enabling universal comparison and analysis across all event types while preserving the specific characteristics of each event type through the vector dimensions.
2Loss of information
If all user events are collected and stored for analysis, then comprehensive user interest estimation can be achieved, but the sheer number of recorded user events renders analysis inefficient or impossible
Solution Approach 1:
The patent extracts essential features from the vast amount of raw user event data and represents them in a compressed vector format. Instead of analyzing all raw event data directly, the system extracts key patterns and characteristics, transforming them into compact vector representations that retain the essential information needed for user interest estimation while dramatically reducing the computational burden of analysis.
Solution Approach 2:
The patent changes the parameter representation of user events from raw, high-dimensional event data to condensed vector representations in a multidimensional space. This parameter transformation allows the system to work with a manageable representation of user events that preserves the essential information for interest estimation while enabling efficient computational processing through the use of vector operations and distance metrics.
3Measurement precision
If multiple vector-mapping modules are used to map user events to different multidimensional spaces, then the analysis capability is enhanced, but the device complexity increases
Solution Approach 1:
The patent segments the complex task of user interest estimation into multiple specialized vector-mapping modules, each responsible for mapping user events to specific multidimensional spaces that capture different aspects of user behavior. This segmentation allows each module to focus on particular dimensions or types of analysis, improving the precision of user interest estimation while organizing the complexity into manageable, modular components that can be independently configured and optimized.
Data Source
AI summary
Computer-implemented method for estimating user interests, executable by a computing device in communication with an output device, comprising: determining a first input vector corresponding to a first user event and a second input vector corresponding to a second user event; mapping first input vector to a first output vector and second input vector to a second 5 output vector in a first multidimensional space using a first vector-mapping module; determining a third input vector based on first output vector and second output vector; mapping third input vector to a third output vector in a second multidimensional space using a second vector-mapping module; determining a message to be provided to a user based on an analysis of at least one of first output vector and third output vector; and causing output 10 device to provide message to user. Also non-transitory computer-readable medium storing program instructions for carrying out the method.