Book similarity calculation method based on random walk and electronic equipment
A random walk and similarity matrix technology, applied in the field of data processing, can solve problems such as poor accuracy, low book adoption rate, and inability to reflect the similarity of books from the user's perspective, so as to optimize the calculation method and improve calculation accuracy Effect
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[0030] Example 1
[0031] figure 1 A schematic flowchart of a method for calculating the similarity of books based on random walks according to Embodiment 1 of the present invention is shown, such as figure 1 As shown, the method includes the following steps:
[0032] Step S101, acquiring user interaction behavior data for the book.
[0033] The user interaction behavior data for a book is data used to describe the interaction between the user and the book, and may specifically include: book reading data, book review data, book download data, etc., for the book by the user. User interaction behavior data implies the law of data changes, which can be used to analyze the relationship between books. In step S101, user interaction behavior data such as book reading data, book review data, and book download data stored in the book reading platform may be obtained from the book reading platform.
[0034] Step S102, according to the user interaction behavior data, determine the s...
Example Embodiment
[0043] Embodiment 2
[0044] figure 2 A schematic flowchart of a method for calculating the similarity of books based on random walks according to the second embodiment of the present invention is shown, such as figure 2 As shown, the method includes the following steps:
[0045] Step S201, acquiring user interaction behavior data for the book.
[0046]Among them, user interaction behavior data such as book reading data, book review data, and book download data of each user for the book can be obtained from the book reading platform. The user interaction behavior data at least includes: user ID, books interacted by the user, interaction start time, interaction termination time and other data. Specifically, the user ID may be the user's account in the book reading platform, such as a mobile phone number, a user name, an email address, a WeChat account, a QQ account, and the like.
[0047] Step S202, for each user, perform data analysis on the user interaction behavior dat...
Example Embodiment
[0085] Embodiment 3
[0086] The third embodiment of the present invention provides a non-volatile storage medium, the storage medium stores at least one executable instruction, and the executable instruction can execute the random walk-based book similarity calculation method in any of the above method embodiments.
[0087] The executable instructions can specifically be used to cause the processor to perform the following operations: acquire user interaction behavior data for books; determine the sequence of interactive books corresponding to each user according to the user interaction behavior data; construct a sequence of interactive books corresponding to each user according to the sequence of interactive books corresponding to each user Book association graph; perform random walk calculation according to the book association graph to obtain the book similarity matrix of each book relative to other books.
[0088] In an optional implementation manner, the executable instr...
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