Content Label Generation via User Search Query Analysis

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Solution Overview

Problem

Existing content delivery systems lack effective methods to categorize and summarize content items for users, making it difficult for users to quickly discern the topic or theme of content items, especially in large collections like news articles or social posts.

Innovation Solution

A machine-implemented method that retrieves and analyzes search terms from user queries to generate labels for content items, ranking them by frequency and relevance, and applying these labels to content items or collections to provide context and categorization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If content items are provided without categorization labels, then the system is simple and easy to operate, but users cannot quickly discern the topic or theme of content items

Engineering Contradiction:

Improveuser ability to quickly discern content topicVSAvoidsystem complexity for label generation

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system performs preliminary analysis of user search queries to extract and store relevant terms before content items need to be categorized. By pre-processing query data and building a term database in advance, the system prepares categorization resources ahead of time, reducing the complexity of real-time label generation while improving user ability to find content by topic.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces search query terms as an intermediary element between user intent and content categorization. These extracted terms serve as intermediate labels that bridge the gap between raw content and user search behavior, enabling automatic categorization without requiring complex manual classification systems.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If manual categorization methods are used, then label accuracy can be maintained, but the process becomes time-consuming and reduces productivity

Engineering Contradiction:

Improvecontent categorization speedVSAvoidlabel accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system enables self-service categorization by automatically analyzing user search queries and generating content labels without human intervention. The algorithm extracts relevant terms from queries and applies them as categorization labels to content items, allowing the system to autonomously perform categorization tasks while maintaining both speed and acceptable accuracy.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system uses user search behavior as feedback to continuously improve categorization accuracy. By analyzing which search terms lead to successful content retrieval and user engagement, the system refines its label generation process, adjusting term selection and weighting based on actual user preferences and search patterns.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS10152543B1Generating content labels according to user search queries

Publication Date: 2018.12.11 GOOGLE LLC

AI summary

In one aspect, a method includes retrieving terms associated with a topic and analyzing the terms based on search results of user queries for content relating to the topic. The method includes selecting one or more terms from the terms based on the analysis. The method includes generating a label from the selected one or more terms and applying the label to a content item relating to the topic. Other aspects can be embodied in corresponding systems and apparatus, including computer program products.