Client-Server Content Recommendation System with Pre-computed Lists

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Solution Overview

Problem

Existing content recommendation systems are slow in generating and delivering content item selections, often resulting in unsatisfactory recommendations, especially for new users without a profile, due to the need for user feedback at the time of request and bandwidth limitations in mobile networks.

Innovation Solution

A client-server system that pre-generates content recommendation lists based on user feedback profiles, allowing immediate delivery of recommendations upon request, with features like streaming and caching to reduce delays and improve user experience, and utilizes a personal radio concept with dynamic playlists and client-server buffering to ensure continuous content delivery.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If the content recommendation system waits for user feedback before generating recommendations, then the recommendations can be personalized, but the system response time increases and new users experience delays

Engineering Contradiction:

Improverecommendation accuracyVSAvoidsystem response time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The server pre-generates content recommendation lists based on existing user feedback profiles before receiving specific requests. When a user requests recommendations, the server can immediately return pre-computed lists without waiting for real-time feedback processing, thus reducing response time while maintaining personalization quality

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system combines pre-computed recommendation lists with real-time user feedback processing. Multiple recommendation lists are generated in advance and merged with current user preferences to create comprehensive, personalized recommendations that balance speed and accuracy

Inventive Principle:

Principle #5Merging (Combining)

2Reliability

If the system generates comprehensive content recommendation lists, then user satisfaction improves, but bandwidth consumption increases in mobile networks

Engineering Contradiction:

Improveuser satisfactionVSAvoidbandwidth consumption

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The recommendation system divides content recommendations into multiple segments or lists with different levels of detail and size. The server can transmit smaller, more focused recommendation lists that consume less bandwidth while still providing sufficient personalization, allowing users to access comprehensive recommendations gradually as needed

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system adjusts the quality and detail level of recommendation lists based on local conditions such as available bandwidth and user device capabilities. In mobile network environments, the server provides optimized, compressed recommendation lists that maintain essential personalization while reducing data transmission requirements

Inventive Principle:

Principle #3Local quality

3Loss of information

If the server processes recommendations in real-time upon request, then data freshness is maintained, but processing delays occur affecting user experience

Engineering Contradiction:

Improvedata freshnessVSAvoidprocessing delay

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The server continuously pre-processes and updates recommendation lists in the background using available user feedback profiles, so that when a user requests recommendations, the data is already prepared and can be transmitted immediately, maintaining both freshness and speed

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The recommendation system operates continuously in the background, constantly updating user profiles and pre-generating recommendation lists based on incoming feedback. This continuous operation ensures that when requests occur, the system can respond immediately with up-to-date recommendations without interruption or delay

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS7756880B2Method of providing content items

Publication Date: 2010.07.13 INTEL CORP

AI summary

A method provides content items located on a server to a client, the server being able to communicate with the client via a communication network. The method includes generating a content recommendation list comprising several content recommendation list entries in dependence on a user feedback profile, each content recommendation list entry representing a content item, and transferring the content recommendation list from the server to the client. The method also includes providing a representation of the content recommendation list entries through a client user interface, each entry being selectable and arranged such that for each entry, user feedback may be generated and corresponding user feedback information sent to the server and that upon selection of an entry at a predetermined position in the content recommendation list, a recommendation list request is transferred to the server.