Image Search Distractiveness Detection via User Behavior Analysis

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Solution Overview

Problem

Current image search engines face challenges in efficiently filtering out distracting results, leading to user inefficiency and distraction, as users often spend time sifting through irrelevant images.

Innovation Solution

A system that monitors user behavior in response to search queries, calculates a distractiveness score for images, and modifies the display order or prominence of images based on this score to prioritize relevant results, using a behavior analyzer to identify and reduce the visibility of distracting content.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If current image search engines display all retrieved images to users, then users can see a comprehensive set of results, but users spend extra time searching through irrelevant images and become distracted

Engineering Contradiction:

Improvenumber of images displayedVSAvoidtime spent searching through results

Core Design Contradiction:

Quantity of substanceVSLoss of time

Solution Approach 1:

The patent extracts and removes distracting images from the search results by calculating a distractiveness score for each image and filtering out those above a threshold. This allows the system to display fewer, more relevant images, reducing the time users spend searching through irrelevant content while maintaining result comprehensiveness.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs preliminary analysis of images by calculating distractiveness scores before displaying results to users. This pre-processing step identifies and flags potentially distracting images in advance, allowing the system to prepare filtered result sets that save users time without requiring post-retrieval filtering.

Inventive Principle:

Principle #10Preliminary action

2Quantity of substance

If current image search engines display all retrieved images to users, then users can see a comprehensive set of results, but users become distracted by irrelevant results

Engineering Contradiction:

Improvenumber of images displayedVSAvoiduser distraction

Core Design Contradiction:

Quantity of substanceVSObject-affected harmful factors

Solution Approach 1:

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system uses seeded images (known distracting content) intentionally included in search results to train and improve the distractiveness detection algorithm. By deliberately exposing users to controlled distracting content, the system learns to better identify and filter such content in future searches, converting the potential harm into a benefit for improving overall result quality.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

3Reliability

If the system monitors user behavior to calculate distractiveness scores, then it can identify and reduce distracting images, but the system complexity increases

Engineering Contradiction:

Improveaccuracy of distracting image detectionVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements a feedback loop where user behavior (clicks, hover time, scrolling patterns) is continuously monitored and fed back into the distractiveness score calculation algorithm. This allows the system to dynamically adjust its detection accuracy based on actual user responses, improving reliability while managing complexity through adaptive rather than static analysis.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system introduces seeded images as intermediaries between the search query and the distractiveness detection process. These known distracting images serve as training data and reference points that simplify the complexity of analyzing all images, providing a controlled subset for calibrating the detection algorithm without requiring full-system complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Reliability

If the system calculates distractiveness scores for all images, then it can filter distracting results effectively, but the processing time and computational resources increase

Engineering Contradiction:

Improveaccuracy of distracting image detectionVSAvoidcomputational resources

Core Design Contradiction:

ReliabilityVSUse of energy by stationary object

Solution Approach 1:

The patent applies partial action by calculating distractiveness scores selectively rather than for all images uniformly. The system uses a two-stage approach: first applying quick heuristics to filter obviously irrelevant images, then applying more computationally intensive analysis only to borderline cases. This reduces overall computational resource consumption while maintaining detection accuracy for the most problematic images.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS7877382B1System and methods for detecting images distracting to a user

Publication Date: 2011.01.25 GOOGLE LLC

AI summary

Methods and apparatus for detecting distracting search engine results are described. In one embodiment, the method includes monitoring the behavior of a user with respect to a group of images that are related in some manner to a query, and using the monitored behavior to calculate the distractiveness of a particular image. The method also includes adding to a group of images related to a query a set of images that are unrelated to the query and monitoring the behavior of a user with respect to all the images.