View source for 20240046119. VALUE CHAIN KNOWLEDGE DISCOVERY METHOD UNDER PERSONALIZED CUSTOMIZATION simplified abstract (GUANGZHOU UNIVERSITY)

=VALUE CHAIN KNOWLEDGE DISCOVERY METHOD UNDER PERSONALIZED CUSTOMIZATION=


==Organization Name==

[[:Category:GUANGZHOU UNIVERSITY|GUANGZHOU UNIVERSITY]]


[[Category:GUANGZHOU UNIVERSITY]]

==Inventor(s)==

[[:Category:Yongjun Hu of Guangzhou (CN)|Yongjun Hu of Guangzhou (CN)]][[Category:Yongjun Hu of Guangzhou (CN)]]

[[:Category:Liuqian Zhu of Guangzhou (CN)|Liuqian Zhu of Guangzhou (CN)]][[Category:Liuqian Zhu of Guangzhou (CN)]]

==VALUE CHAIN KNOWLEDGE DISCOVERY METHOD UNDER PERSONALIZED CUSTOMIZATION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240046119 titled 'VALUE CHAIN KNOWLEDGE DISCOVERY METHOD UNDER PERSONALIZED CUSTOMIZATION

==Simplified Explanation==

The patent application describes a method for discovering knowledge in a value chain under personalized customization. Here is a simplified explanation of the abstract:

* Defining a value topic and extracting a seed word that represents the value in a given domain text.
* Constructing a semantic topological space based on the seed word to represent the value.
* Expanding the seed word to create an initial set of words that anchor the topic.
* Updating the initial set of words to optimize the anchoring of the topic.
* Representing the value semantic text as a multi-cluster net structure using the optimized anchoring words as a constraint.
* Anchoring and constraining multiple cross-domain texts to construct a knowledge graph of the value chain.

Potential applications of this technology:

* Knowledge discovery and analysis in various industries and domains.
* Personalized customization of value chains in e-commerce or service industries.
* Semantic analysis and understanding of value-related texts for market research or competitive analysis.

Problems solved by this technology:

* Efficiently identifying and extracting valuable information from large amounts of text data.
* Personalizing and customizing value chains to meet individual needs and preferences.
* Creating a structured representation of value-related knowledge for analysis and decision-making.

Benefits of this technology:

* Improved efficiency in knowledge discovery and analysis.
* Enhanced personalization and customization of value chains.
* Better understanding of value-related information for informed decision-making.
* Facilitation of market research and competitive analysis.


==Original Abstract Submitted==

a value chain knowledge discovery method under personalized customization is provided. the method comprises the following steps: defining a value topic for a given domain text, and extracting a value anchoring seed word; constructing a value semantic topological space according to the value anchoring seed word; expanding the value anchoring seed word to obtain an initial topic anchoring word set; updating the initial topic anchoring word to obtain an optimized topic anchoring word set; obtaining a multi-cluster net structure representation of a value semantic text by taking the optimized topic anchoring word as a constraint; and anchoring and constraining a plurality of cross-domain texts to construct a value chain knowledge graph.



[[Category:G06N5/022]]