Personalized book searching method based on interactive evolutionary optimization

Abstract

The invention discloses an interactive evolutionary optimization method for personalized and quick searching on psychological graphs, and aims to instruct a user to quickly search satisfactory books and relieve the searching fatigue of the user. The method specifically comprises the steps of (1) supplying initialized information according to information input by the user, namely generating an initial population in an interactive genetic algorithm; (2) performing human-machine interaction, namely performing an interaction behavior by the user according to an evolutionary phenotype displayed by a system, such as clicking and browsing a few of interested contents; (3) performing interaction behavior-based CP-nets preference modeling and updating so as to acquire and track a preference change according to the interaction behavior of the user; (4) performing an interactive evolutionary process based on CP-Nets, namely performing adaptation value evaluation on searching information represented by the current evolutionary population according to CP-nets, and executing selection, intercrossing and variation operations so as to generate new individual information which can meet the preference of the user.

Description

technical field [0001] This patent belongs to the field of intelligent computing, and is a book personalized search method based on an interactive evolutionary optimization strategy, which can be used to guide users to quickly search books in a network environment. Background technique [0002] In real life, evaluation and decision-making optimization problems that require human participation exist widely. For example, in the formulation of travel plans, different people have different comprehensive evaluations of travel routes, transportation methods, time, costs, etc., and thus formulate different travel routes. The above problem is an optimization problem. However, due to the need for human participation, it cannot be described by an accurate mathematical model, so traditional optimization based on mathematical functions and various intelligent optimization algorithms are no longer applicable. The interactive evolutionary optimization algorithm integrated with human inte...

AI Technical Summary

Problems solved by technology

After reviewing relevant literature, there is no precedent for applying this technology to book personalized search. If a set of efficient search methods can be designed for the book personalized search problem, it will greatly reduce the search volume of users and improve search efficiency. At the same time, it can also be considered to be extended to personalized search in other fields to achieve greater social benefits

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