Prediction Center Consolidating Mobile Prediction Engines
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional techniques for predicting user behavior on mobile computing devices gather and analyze data in a disorganized manner, leading to inaccurate and cumbersome suggestions, and are difficult to update, limiting software developers' ability to enhance prediction accuracy and performance.
Innovation Solution
Implementing a prediction center that manages multiple prediction engines, which assign themselves as experts on specific categories, aggregates and optimizes predictions by removing duplicates, sorting by confidence levels, and providing synchronized or asynchronous predictions to software applications, thereby improving user experience and device performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional techniques gather and analyze behavioral data in a disorganized manner, then data collection is simple, but prediction accuracy deteriorates
Solution Approach 1:
The patent segments the prediction system into multiple specialized prediction engines, each responsible for specific prediction categories (e.g., contacts, messages, media players). This segmentation allows organized collection and analysis of behavior data for different domains, improving prediction accuracy while maintaining manageable complexity through clear division of responsibilities.
Solution Approach 2:
The prediction center serves as an intermediary component that receives behavior data from multiple sources, organizes it systematically, and distributes it to appropriate prediction engines. This intermediary structure provides the necessary data organization framework without requiring complete reorganization of the entire system, thus improving prediction accuracy while controlling complexity.
2Adaptability or versatility
If conventional techniques are implemented at layers within the operating system that are difficult to update, then system stability is maintained, but adaptability deteriorates
Solution Approach 1:
The patent implements a segmented architecture where prediction engines are separate, modular components that can be independently updated and developed by software developers. This segmentation allows frequent updates and improvements to prediction techniques without affecting the stability of the core operating system, thus improving adaptability while managing complexity through clear boundaries.
Solution Approach 2:
The prediction center provides a universal interface and data collection mechanism that serves multiple specialized prediction engines. This multi-functional component enables different prediction techniques to be updated independently while sharing common infrastructure, improving adaptability without proportionally increasing overall system complexity.
3Adaptability or versatility
If multiple prediction engines provide predictions, then prediction coverage is improved, but processing complexity deteriorates
Solution Approach 1:
The prediction center acts as an intermediary that receives predictions from multiple specialized engines, consolidates them, and presents a unified set of predictions to applications. This intermediary structure allows comprehensive prediction coverage across multiple categories while managing processing complexity through centralized coordination and standardization of prediction formats.
Solution Approach 2:
The patent merges predictions from multiple specialized engines into a unified prediction set through the prediction center. This combining process consolidates redundant information, resolves conflicts between different engines, and presents a streamlined set of predictions to applications, thus maintaining comprehensive coverage while reducing processing complexity.
Data Source
AI summary
The embodiments set forth techniques for implementing various “prediction engines” that can be configured to provide different kinds of predictions within a mobile computing device. According to some embodiments, each prediction engine can assign itself as an “expert” on one or more “prediction categories” within the mobile computing device. When a software application issues a request for a prediction for a particular category, and two or more prediction engines respond with their respective prediction(s), a “prediction center” can be configured to receive and process the predictions prior to responding to the request. Processing the predictions can involve removing duplicate information that exists across the predictions, sorting the predictions in accordance with confidence levels advertised by the prediction engines, and the like. In this manner, the prediction center can distill multiple predictions down into an optimized prediction and provide the optimized prediction to the software application.