Intellectual Property India Publishes Patent Application for Intelligent Aspect-Based Sentiment Analysis System For Brand Reputation Monitoring And Marketing Strategy Optimization

MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202631115002 A) filed by Dr. Deepti Ranjan Sabat; Kuchana Nagarani; Dr. Chitra; Udaya Kiran P; Dr. Neha Gupta; Gorukanti Sandhya; G Bikshapathi; Gundu Radika; and Dr. Someshwar. S on September 25, 2026, for Intelligent Aspect-Based Sentiment Analysis System For Brand Reputation Monitoring And Marketing Strategy Optimization.

Inventors include Dr. Deepti Ranjan Sabat; Kuchana Nagarani; Dr. Chitra; Udaya Kiran P; Dr. Neha Gupta; Gorukanti Sandhya; G Bikshapathi; Gundu Radika; and Dr. Someshwar. S.

The application for the patent was published on October 02, 2026, under issue no. 40/2026.

Abstract: The present invention provides a computer-implemented system and method for aspect-based sentiment analysis and temporal brand reputation monitoring. Heterogeneous textual feedback is received from multiple sources and subjected to normalization, language processing, duplicate detection and contextual segmentation. An aspect and context extraction engine identifies a target entity and associated aspects, while a sentiment inference engine determines aspect-level polarity, intensity and confidence. A temporal reputation fusion engine generates duplicate-adjusted, confidence-weighted and time-dependent aspect reputation signals using source and recency information. A change detection module compares the generated signals with computational baselines to identify trend shifts, anomalies or change points. An explainable alert generation module produces an evidence-linked output containing affected aspects, temporal changes, confidence information and source references. A domain knowledge store and validated feedback mechanism can update aspect vocabulary and inference parameters while maintaining versioned audit information. The system thereby provides a technical pipeline for granular, traceable and temporal analysis of textual reputation signals across heterogeneous data sources. Accompanied Drawing [FIGS. 1-2].

Disclaimer: Curated by HT Syndication.