Object Relationship Networks From Regulation Keyword Similarity
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Solution Overview
Problem
Existing manual management of multiple regulations in enterprises is labor-intensive and lacks an accurate mathematical model to quantify the relationship between them, leading to inefficiency and difficulty in managing complex associations.
Innovation Solution
Construct an object relationship network by extracting keywords from regulation documents using text processing techniques, determining similarities between regulations, and building a network based on these similarities to describe the closeness of relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual management methods are used to manage multiple regulations, then management can be performed, but labor costs are high and management efficiency is low
Solution Approach 1:
The system enables automatic extraction of keywords from regulation texts using text processing techniques, automatically determines similarity between regulations, and automatically constructs the regulation relationship network without requiring manual intervention for each regulation, thereby reducing labor costs and improving management efficiency
Solution Approach 2:
The patent replaces manual mechanical management processes with automated computational methods including text processing, similarity calculation algorithms, and automatic network construction, substituting human labor with machine-based automated systems
2Measurement precision
If manual management methods are used, then management can be performed, but there is no accurate mathematical model to quantify relationships between regulations
Solution Approach 1:
The patent transforms qualitative regulatory relationships into quantitative measurements by calculating similarity values between regulations based on keyword overlap and text processing results, providing an accurate mathematical model to quantify relationships that was previously unavailable
Solution Approach 2:
The patent introduces an intermediary computational layer that processes regulation texts, extracts keywords, calculates similarities, and constructs the relationship network, serving as a mediator between raw regulation data and the final quantified relationship model
3Productivity
If automated text processing is used to extract keywords and construct relationships, then management efficiency is improved, but the complexity of the system increases
Solution Approach 1:
The patent segments the complex task of regulation management into distinct modular components: text processing module, keyword extraction module, similarity calculation module, and network construction module, making the system more manageable and maintainable despite its automation capabilities
Solution Approach 2:
The patent creates a universal automated framework that can handle multiple regulations simultaneously using the same text processing and similarity calculation methods, allowing the system to scale without proportionally increasing complexity
Data Source
AI summary
A method and an apparatus for constructing an object relationship network and an electronic device are provided by the present disclosure, relating to the field of artificial intelligence technologies, such as deep neural networks, deep learning, etc. A specific implementation solution is: extracting keywords in respective text contents corresponding to a plurality of objects to obtain keywords corresponding to respective objects; and according to the keywords corresponding to the objects, a similarity between the plurality of objects is determined; and then according to the similarity between the plurality of objects, an object relationship network between the plurality of objects is constructed. Since the object relationship network constructed by means of the similarity between the plurality of objects can accurately describe a closeness degree of a relationship between the objects, thus, the plurality of objects can be managed effectively by means of the constructed object relationship network.