18421095. SYSTEMS AND METHODS FOR IDENTIFYING AND ANALYZING RISK EVENTS FROM DATA SOURCES simplified abstract (Tata Consultancy Services Limited)
Contents
SYSTEMS AND METHODS FOR IDENTIFYING AND ANALYZING RISK EVENTS FROM DATA SOURCES
Organization Name
Tata Consultancy Services Limited
Inventor(s)
CHARLES Njelita of Edison NJ (US)
SUKADEV Khatua of Bhubaneswar (IN)
SYSTEMS AND METHODS FOR IDENTIFYING AND ANALYZING RISK EVENTS FROM DATA SOURCES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18421095 titled 'SYSTEMS AND METHODS FOR IDENTIFYING AND ANALYZING RISK EVENTS FROM DATA SOURCES
- Simplified Explanation:**
The patent application describes a system and method for identifying and analyzing risk events from data collected from various sources. Key phrases are clustered based on word frequency and classified into categories. Events and topics are identified and grouped to obtain high-risk entities with a risk score.
- Key Features and Innovation:**
- System for identifying and analyzing risk events from social media data
- Clustering of key phrases based on word frequency
- Classification of clustered data into categories
- Analysis of specific category datasets to identify high-risk events
- Ranking and assigning risk scores to entities
- Simulation and optimization techniques for analyzing high-risk events
- Potential Applications:**
This technology can be applied in risk management, crisis response, and event monitoring in social media platforms.
- Problems Solved:**
The technology addresses the challenge of accurately identifying and analyzing risk events from social media data, providing a more reliable method for risk assessment.
- Benefits:**
- Improved accuracy in identifying high-risk events
- Enhanced risk management and crisis response capabilities
- Efficient monitoring of events and topics on social media platforms
- Commercial Applications:**
Potential commercial applications include social media monitoring tools for risk assessment, crisis management software, and event analysis platforms for businesses and organizations.
- Prior Art:**
Prior art related to this technology may include existing systems for sentiment analysis and event detection in social media data.
- Frequently Updated Research:**
Research on sentiment analysis, event detection, and risk assessment in social media data may provide valuable insights for further development of this technology.
- Questions about social media risk analysis:**
1. How does this technology improve upon traditional sentiment analysis methods for social media data? 2. What are the potential implications of using this system for risk management in social media platforms?
Original Abstract Submitted
Conventional methods of analyzing social media content involves performing sentimental analysis to understand related sentiment and effects of events on communities. However, such analysis may not be completely accurate and are prone to errors. Present disclosure provides system and method that identify and analyze risk events from data collected from various sources. Key phrases obtained from sources is received, pre-processed, and clustered accordingly. The clustering is performed based on frequency of incoming words. The clustered dataset obtained is classified into one or more categories based on a polarity score. Dataset of specific category (e.g., negative category dataset) is analysed to identify events and topics which are then grouped using an associated label to obtain grouped entities. Each entity is then ranked and assigned a risk score for identifying high-risk events which are then analyzed using simulation and optimization technique(s) and an explainability text for the analyzed risk events is generated.
