Sentiment Trend Analysis via Term Taxonomy Segmentation

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Solution Overview

Problem

Current search systems fail to effectively distinguish between relevant and irrelevant information on the internet, particularly in identifying sentiment trends and meaningful relationships in user-generated content, leading to difficulties in targeting advertisements and understanding human behavior dynamically.

Innovation Solution

A system for analyzing sentiment trends based on term taxonomies, which includes a network interface, a mining unit for collecting and generating phrases, a data warehouse for storage, and an analysis unit for generating associations and statistical trends, enabling real-time reporting and notification of sentiment trends in user-generated content.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If search systems collect and store all available user-generated content, then the quantity of information increases, but the quality and relevance of information decreases

Engineering Contradiction:

Improvequantity of informationVSAvoidinformation quality

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent segments information into structured taxonomies with hierarchical categories (e.g., product categories, sentiment categories, topic categories). This segmentation allows the system to organize vast quantities of user-generated content into manageable, relevant groups, improving information quality without losing the breadth of data collection.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent extracts specific meaningful elements (sentiment indicators, product mentions, topic keywords) from unstructured user-generated content through natural language processing. This extraction process separates valuable information from noise, maintaining high information quality while preserving the ability to analyze large volumes of data.

Inventive Principle:

Principle #2Taking out (Extraction)

2Device complexity

If search systems perform static analysis of information, then the simplicity of the system is maintained, but the ability to understand dynamic human trends decreases

Engineering Contradiction:

Improvesystem simplicityVSAvoiddynamic trend understanding

Core Design Contradiction:

Device complexityVSAdaptability or versatility

Solution Approach 1:

The patent implements dynamic sentiment analysis that continuously updates taxonomy classifications and sentiment scores as new user-generated content is processed. The system adapts to changing trends by re-evaluating sentiment associations and updating statistical analyses over time, enabling dynamic trend understanding while maintaining a relatively simple architectural framework.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent incorporates feedback loops where sentiment analysis results and statistical trends are fed back into the taxonomy structure and analysis models. This feedback mechanism allows the system to learn from accumulated data and improve its dynamic trend understanding without requiring complete system redesign.

Inventive Principle:

Principle #23Feedback

3Loss of information

If search systems provide comprehensive information without analysis, then the completeness of information is maintained, but the usefulness for targeted advertising decreases

Engineering Contradiction:

Improveinformation completenessVSAvoidadvertising effectiveness

Core Design Contradiction:

Loss of informationVSReliability

Solution Approach 1:

The patent performs preliminary sentiment analysis and taxonomy classification on user-generated content before it is needed for advertising decisions. By pre-processing and structuring the information in advance, the system maintains complete information while making it immediately usable for targeted advertising campaigns without loss of completeness.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces sentiment taxonomies and statistical analysis layers as intermediaries between raw user-generated content and advertising applications. These intermediaries transform unstructured data into actionable insights while preserving the underlying complete information set for reference.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Quantity of substance

If search systems require users to sift through large amounts of information, then the comprehensiveness of search results is maintained, but the time required to find meaningful information increases

Engineering Contradiction:

Improvesearch result comprehensivenessVSAvoidinformation retrieval time

Core Design Contradiction:

Quantity of substanceVSLoss of time

Solution Approach 1:

The patent adds dimensional organization to search results through multi-level taxonomies (product categories, sentiment dimensions, topic categories, time periods). This dimensional structuring allows users to navigate comprehensive information sets through multiple filtering dimensions simultaneously, dramatically reducing retrieval time while maintaining result comprehensiveness.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS8965835B2Method for analyzing sentiment trends based on term taxonomies of user generated content

Publication Date: 2015.02.24 INNOVID INC

AI summary

A method for generating a trend report for a non-sentiment phrase. The method comprises generating a plurality of term taxonomies between non-sentiment phrases and sentiment phrases; storing the plurality of term taxonomies in a database; performing periodically at least a statistical analysis respective of the plurality of term taxonomies in the database; receiving a request for a report with respect of at least a non-sentiment phrase in the database; generating a trend report based at least on the at least statistical analysis; and providing the report to the requestor of the report.