Peer-to-Peer Music Recommendation System with Feedback-Driven Profile Updates
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Solution Overview
Problem
Existing systems lack an efficient method for users to generate and transmit music recommendation requests to peers and obtain relevant music recommendations within a peer-to-peer music recommendation service.
Innovation Solution
A computer-implemented method and system that allows users to specify music recommendation requests with tags, transmit these requests to selected peers, and receive relevant music recommendations, while also updating user profiles based on feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually search for music recommendations, then they can obtain relevant music suggestions, but the process is time-consuming and inefficient
Solution Approach 1:
The system enables users to request music recommendations from their peer network without manual searching. Users simply specify their music preferences and the system automatically distributes requests to selected peers, collects recommendations, and presents relevant results, eliminating the need for users to manually search through extensive music libraries.
Solution Approach 2:
The system incorporates feedback mechanisms where users provide input about their music preferences and the system uses this feedback to refine recommendation requests sent to peers. The feedback loop continues as users interact with recommended music, allowing the system to improve future recommendations based on actual user responses and preferences.
2Adaptability or versatility
If the system transmits recommendation requests to multiple peers, then the variety of music recommendations increases, but the complexity of managing and processing requests increases
Solution Approach 1:
The system segments the recommendation process by allowing users to select specific peers from their network to receive recommendation requests. Instead of managing all possible connections, users can segment their request distribution to a manageable subset of peers who are most likely to provide relevant recommendations based on their musical preferences and relationship with the requesting user.
Solution Approach 2:
The system acts as an intermediary that handles the complexity of transmitting and collecting recommendation requests from multiple peers. The system automatically manages the communication protocol, collects recommendations from selected peers, filters relevant results, and presents them to the user, eliminating the need for users to directly manage complex multi-peer communication.
3Measurement precision
If the system updates user profiles based on feedback, then the relevance of future recommendations improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary profile updates during the recommendation collection process rather than waiting for separate feedback analysis phases. As users interact with recommended music and provide feedback, the system immediately processes this information to update relevant user profiles and peer preferences in real-time, preparing the system for future recommendation requests without requiring separate batch processing periods.
Data Source
AI summary
Disclosed embodiments provide a framework to allow users of a peer-to-peer music recommendation service to generate and transmit music recommendation requests to other users of the service and obtain music recommendations that are relevant to these requests. In response to receiving a request to obtain music recommendations, the service transmits the request to a set of recipients specified in the request and from which music recommendations are to be solicited. The request specifies information that is indicative of the types of music being solicited. A recommendation received from a recipient includes identifying information of a song accessible via another music service and information indicative of a type of music of the song. Any received recommendations are presented in response to the request and feedback with regard to these recommendations is collected. Based on the provided feedback, profiles of the recipients that submitted the recommendations are updated.