Automatic Application Selection via Social Contacts
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Solution Overview
Problem
Mobile devices face resource strain due to the pre-installation of numerous applications, many of which are unused, leading to wasted resources and an overwhelming choice for users.
Innovation Solution
A method for automatically installing only the most relevant applications on a user device based on user identification and preferences derived from their contacts, using a social service to select and install a subset of applications from a larger set, thereby personalizing the device and conserving resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If numerous applications are pre-installed on mobile devices, then service providers can deliver sophisticated applications and services, but resource strain on end user devices increases
Solution Approach 1:
The system performs preliminary action by automatically selecting and installing relevant applications before the user needs them, based on pre-configured user profiles and contact information. This eliminates the need for users to manually browse and install applications, reducing resource strain while ensuring appropriate applications are available.
Solution Approach 2:
The system enables self-service by allowing user profiles and contact information to automatically determine which applications should be installed. The device serves itself by using stored user data to make intelligent application selection decisions, reducing the need for manual user intervention and minimizing resource consumption.
2Adaptability or versatility
If many applications are installed on mobile devices, then wide ranging services are provided, but device complexity increases
Solution Approach 1:
The system extracts only the necessary applications from the available pool based on user profiles and contact information. Instead of installing all possible applications, it selectively extracts and installs only those relevant to the specific user, reducing device complexity while maintaining service coverage.
Solution Approach 2:
The system applies local quality by customizing the application set for each individual user based on their specific profile and contact information. Each user receives a tailored set of applications appropriate to their needs, rather than a universal set, reducing overall device complexity while maintaining adaptability.
3Adaptability or versatility
If users manually select applications from a large number of available applications, then personalized device configuration is achieved, but user time and effort increase
Solution Approach 1:
The system performs preliminary action by pre-configuring user profiles and contact information, which are then automatically used to select appropriate applications. This eliminates the time-consuming manual selection process while maintaining personalized device configuration.
Solution Approach 2:
The system uses feedback from stored user profiles and contact information to automatically determine which applications to install. This closed-loop approach uses existing user data to make intelligent selection decisions, achieving personalization without requiring additional user time or effort.
4Loss of energy
If automatic application selection is implemented, then resource waste is reduced, but system complexity increases
Solution Approach 1:
The system reduces resource waste through self-service automation, where user profiles and contact information automatically determine application selection. This eliminates manual intervention and reduces resource waste while the automation leverages existing data structures to minimize added system complexity.
Solution Approach 2:
The system achieves multi-functionality by using the same user profile and contact information infrastructure for multiple purposes: contact management, application selection, and personalization. This universal approach reduces resource waste without proportionally increasing system complexity, as the same data serves multiple functions.
Data Source
AI summary
An approach is provided for automatic loading of applications, including receiving user identification corresponding to a device. Data is also received, which indicates a set of one or more relevant applications that are a subset of multiple available applications. The set is automatically selected based on the user identification and an application favored by a contact associated with the user. Installation is initiated of an application of the selected set within the device. In some embodiments, access is provided to a social service via a network. The social service includes data that indicates multiple users, contacts among the users, and applications favored by the users. Access is also provided to receive at the social service a request message indicating user identification for a first user at a first network node. A message indicating a relevant application based on an application favored by a contact of the first user is transmitting to the first network node.