Entity Association Identification via Multi-Attribute Probability Scoring
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Solution Overview
Problem
Conventional methods for retrieving information about an entity face challenges such as outdated, unverified, and irrelevant data due to the vast volume of internet data, requiring a more efficient and reliable approach to identify relevant associations.
Innovation Solution
A system and method that utilize a processing module to receive input data, acquire web content from multiple sources, filter and analyze it using an ontology to determine recency, frequency, proximity, and semantics attributes, and calculate a probability score to identify the most relevant association.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large scale crawling is used to retrieve information from the Internet, then the volume of retrieved data increases, but the data becomes outdated and less relevant
Solution Approach 1:
The patent changes the parameters of data evaluation by introducing multiple attributes (recency, frequency, proximity, semantics) and calculating probability scores to dynamically assess and rank associations, transforming static data retrieval into a dynamic, multi-parameter evaluation process that resolves the contradiction between data volume and data quality
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring and re-evaluating associations based on updated attributes, where the probability scores are recalculated as new data becomes available, ensuring that the most relevant and current information is consistently identified despite the vast volume of available data
2Reliability
If manual inquiry is used to obtain information from data sources, then the accuracy of information increases, but the time and labor required increases significantly
Solution Approach 1:
The patent replaces manual mechanical inquiry processes with an automated computer-implemented system that uses algorithms to evaluate associations and calculate probability scores, maintaining high accuracy while eliminating the time and labor constraints of manual methods
Solution Approach 2:
The system performs self-service by automatically acquiring data from multiple sources, evaluating associations, and identifying the most relevant information without requiring manual intervention, thereby achieving manual-level accuracy with automated efficiency
3Adaptability or versatility
If crawler retrieves data from multiple data sources, then the comprehensiveness of information increases, but the difficulty of identifying relevant information increases
Solution Approach 1:
The patent segments the complex task of identifying relevant information by evaluating multiple distinct attributes (recency, frequency, proximity, semantics) separately and then integrating them through probability score calculation, making the overall process more manageable and systematic
Solution Approach 2:
The probability score acts as an intermediary that synthesizes multiple attribute evaluations into a single ranked output, mediating between the comprehensive but diverse data from multiple sources and the need to identify the most relevant associations
Data Source
AI summary
A system and method for identifying at least one association of an entity. The system includes a processing module and a database arrangement communicably coupled to processing module. The processing module is operable to receive an input comprising data related to the entity; acquire web content related to the received input from a plurality of data sources; filter the acquired web content to obtain information relating to the entity; identify probable associations of the entity from the information relating to the entity using an ontology; determine for each of the probable associations, at least one of: a recency attribute, a frequency attribute, a proximity attribute, a semantics attribute; determine a probability score for each of the probable associations of the entity; and identify the at least one association of the entity from the probable associations, wherein the at least one association corresponds to a highest probability score.