User Search Behavior Data Mining for Financial Instrument Matching
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Solution Overview
Problem
Current data mining technologies face challenges in effectively analyzing and understanding the search behavior of a large number of users to determine their financial needs, which is crucial for providing relevant financial instruments.
Innovation Solution
A method and apparatus that acquire and analyze search behavior information to determine financial instruments and user attention, grouping users based on financial need characteristics and matching them with appropriate financial instruments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data mining is performed on search behavior of a large number of users, then user needs can be determined, but the complexity of analyzing and understanding search behavior increases
Solution Approach 1:
The patent segments the complex data mining process into distinct modules: search behavior acquisition module, search behavior analysis module, user needs determination module, and financial instrument matching module. This segmentation allows each module to handle specific tasks independently, reducing overall system complexity while maintaining accurate user needs determination through coordinated module operations.
2Loss of information
If search behavior information of many users is analyzed, then financial needs can be identified, but the time and computational resources required increase
Solution Approach 1:
The patent implements preliminary action by pre-processing search behavior data into structured formats, pre-categorizing user search patterns, and pre-establishing financial instrument databases with standardized characteristics. This preliminary preparation reduces the time and computational resources needed during actual user needs analysis while maintaining complete information coverage.
3Adaptability or versatility
If users are grouped based on financial need characteristics, then personalized financial instruments can be provided, but the complexity of matching users with instruments increases
Solution Approach 1:
The patent applies parameter changes by transforming user financial need characteristics into standardized parameters and financial instrument characteristics into corresponding parameters. This parameter standardization enables automated matching algorithms to efficiently compare and match users with suitable financial instruments based on parameter compatibility, reducing matching system complexity while maintaining high personalization levels.
Data Source
AI summary
A method for performing data mining based on search behavior of a user is provided. One embodiment includes acquiring search behavior information of users; determining financial instruments corresponding to search behavior of the user and determining user attention information corresponding to each of the determined financial instruments. Another embodiment includes acquiring search behavior information of users; determining financial need related characteristics of the users; and grouping the users into user groups according to the determined financial need related characteristics; and determining a financial instrument corresponding to each of the user groups by matching the financial need related characteristic of each of the user groups with instrument characteristics of financial instruments. By implementing the methods, accurate and objective data support can be provided for financial institutions to provide financial instruments that meet user needs and financial instruments that meet the users' actual needs can be provided.