Social Event Recommendation Engine Personalization

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Solution Overview

Problem

Current location-aware applications fail to consider users' preferences and relationships when recommending social events, leading to a lack of personalized and relevant event suggestions.

Innovation Solution

A social event recommendation engine that utilizes user profile databases and social event databases to suggest events based on users' interests, geographic location, and relationships, allowing for personalized invitations and integrated advertisements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If location-aware applications use simple check-in mechanisms with coupons and virtual points, then user participation is encouraged, but the recommendations lack personalization and relevance to user preferences and relationships

Engineering Contradiction:

Improvepersonalization of event recommendationsVSAvoidsystem complexity for processing user profiles and relationships

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by collecting and storing user profile information, friend relationships, and event characteristics in databases before making recommendations. User profiles include interests, demographics, and social connections that are pre-processed and stored for later retrieval during recommendation generation, eliminating the need for complex real-time analysis

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces a recommendation engine as an intermediary component that sits between the user and the event database. This engine processes user profiles and event characteristics separately, then combines them to generate personalized recommendations, thereby managing system complexity through modular architecture rather than monolithic processing

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If the system integrates user profiles, friend relationships, and event characteristics for personalized recommendations, then recommendation quality improves, but processing time and computational resources increase

Engineering Contradiction:

Improveaccuracy of event recommendationsVSAvoidtime for generating recommendations

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

User profiles, friend relationships, and event characteristics are pre-collected and stored in databases before recommendation generation. This preliminary organization of data allows the recommendation engine to quickly retrieve and match information without performing complex real-time computations, thereby maintaining high accuracy while reducing processing time

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The recommendation system is segmented into distinct functional modules: user profile management, friend relationship tracking, event characteristic storage, and recommendation generation. Each module operates independently and stores its data separately, allowing parallel processing and reducing the time required to generate comprehensive personalized recommendations

Inventive Principle:

Principle #1Segmentation

3Adaptability or versatility

If the system provides comprehensive social event recommendations with friend suggestions and advertisements, then user engagement increases, but the interface becomes more complex

Engineering Contradiction:

Improvecomprehensiveness of social event recommendationsVSAvoiduser interface simplicity

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The recommendation output is segmented into distinct visual components: event details, friend suggestions, and advertisements are presented as separate elements in the user interface. This segmentation allows users to process information in manageable chunks and selectively engage with different parts of the recommendation, maintaining interface simplicity while providing comprehensive information

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The recommendation engine acts as an intermediary that organizes and filters information before presentation to the user. It processes comprehensive data about events, friends, and advertisements, then presents them in a structured, user-friendly format that maintains simplicity while delivering comprehensive recommendations

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS9602606B2Systems and methods for a social facilitator service

Publication Date: 2017.03.21 ADEIA GUIDES INC

AI summary

Systems and methods for providing social event recommendations to a user are provided. In particular, a user may be presented with recommendations for social events based on the user's interests, geographic location, or any other suitable constraints. A social event recommendation engine may additionally suggest friends, from the user's social network, that the user may wish to invite along to a recommended social event. The user may also be presented advertisements with the social event recommendations.