Mobile Application Recommendation via Messaging Intermediary
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Solution Overview
Problem
Users of mobile stations face difficulty in finding relevant applications due to growing catalogs, and existing recommendation systems are limited in where and when applications can be recommended.
Innovation Solution
A method and system that allows end-users to recommend mobile station applications by sending a messaging service message through a mobile communication network, identifying capable devices, and transmitting the application for download, with features like price determination and compatibility checking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If application catalogs continue to grow to provide more applications, then application variety increases, but user ability to locate relevant applications deteriorates
Solution Approach 1:
The patent introduces a recommendation message system that acts as an intermediary between application providers and users. Users receive targeted application recommendations through messaging services, which guide them to relevant applications without requiring them to search through growing catalogs manually.
Solution Approach 2:
The system implements feedback mechanisms where users can rate and comment on applications. This feedback loop allows the system to learn user preferences and improve recommendation accuracy, helping users locate relevant applications more efficiently as catalogs grow.
2Productivity
If existing recommendation systems are used (word of mouth, social networking, comments), then some application promotion occurs, but recommendation flexibility and accessibility are limited
Solution Approach 1:
The patent creates a universal recommendation system that works across multiple communication channels and device types. The messaging service infrastructure enables application recommendations to be sent through existing messaging networks, making the system adaptable to various user contexts and communication preferences.
Solution Approach 2:
The system dynamically adapts recommendation delivery based on user behavior, device capabilities, and communication preferences. Recommendations can be sent through different messaging services and adjusted based on user responses, making the recommendation process flexible and responsive to changing conditions.
3Productivity
If application recommendations are sent to all mobile stations, then maximum exposure is achieved, but compatibility issues increase
Solution Approach 1:
The system performs preliminary compatibility checking by analyzing device identifiers and characteristics before sending application recommendations. This preliminary action filters out incompatible devices, ensuring that recommendations are only sent to mobile stations capable of executing the recommended applications.
Solution Approach 2:
The patent applies local quality by tailoring recommendations to specific device characteristics and user profiles. Instead of uniform recommendations, the system adapts application suggestions to match individual device capabilities and user preferences, improving both exposure effectiveness and compatibility.
Data Source
AI summary
Systems and methods for recommending an application from a mobile station are shown and described. Components of the network and components in communication with the network cooperate to confirm whether a mobile station recommended to receive the application is capable of executing the application and provisioning the application for transmission to the recommended mobile station.