Mobile Destination Recommendation System Using Historical Behavior Data
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Solution Overview
Problem
Current location-based service (LBS) platforms require manual input of destinations, which is time-consuming, and there is a need for systems and methods to automatically recommend destinations based on user behavior and current time to improve efficiency.
Innovation Solution
A system and method that remotely operates a mobile device's interface to receive LBS requests, obtain historical behavior information, and determine recommended destinations based on this data, then displays these recommendations on the device's interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual input of destination is required in LBS platforms, then user can specify exact destination, but it is time-consuming
Solution Approach 1:
The system pre-processes historical behavior information and calculates probability scores for multiple potential destinations before the user makes a request. When the user triggers the recommendation function, the system quickly retrieves and presents the pre-calculated recommended destinations, avoiding real-time computation delays while maintaining high accuracy.
Solution Approach 2:
The system automatically analyzes the user's historical behavior data, current location, and contextual information to generate destination recommendations without requiring manual input from the user. The user simply needs to trigger the recommendation function, and the system self-serves by presenting the most likely destinations based on the user's past patterns.
2Productivity
If automatic destination recommendation is implemented, then time efficiency is improved, but system complexity increases
Solution Approach 1:
The system introduces a recommendation module as an intermediary between the user and the destination database. This module processes historical behavior information, calculates probabilities, and presents filtered recommendations, simplifying the user interface while managing the complexity of data processing in the background.
Solution Approach 2:
The system divides the destination recommendation process into separate functional modules: historical data collection, probability calculation, recommendation generation, and result presentation. This modular architecture allows each component to be optimized independently, reducing overall system complexity while maintaining high productivity.
3Measurement precision
If historical behavior information is analyzed, then recommendation accuracy is improved, but data processing requirements increase
Solution Approach 1:
The system calculates probability scores for only the top N most likely destinations based on historical behavior patterns, rather than analyzing all possible destinations. This partial action approach maintains high recommendation accuracy by focusing computational resources on the most probable outcomes, reducing overall energy consumption.
Solution Approach 2:
The system dynamically adjusts the depth of historical data analysis and probability calculation based on available computational resources and user preferences. When energy is constrained, the system uses simplified models with fewer parameters; when resources are abundant, it performs more comprehensive analysis to improve accuracy.
Data Source
AI summary
The present disclosure relates to systems and methods for remotely operating an interface of a mobile device. The method may include receiving a request for an LBS sent from the mobile device through the information exchange port, and obtaining a current time point in response to the request for the LBS. The method may also include obtaining historical behavior information related to a user of the mobile device. The method may also include determining, based on the historical behavior information and the current time point, one or more recommended destinations for the user. The method may further include remotely controlling the interface of the mobile device, through the information exchange port, to display the one or more recommended destinations.