It is technically feasible to analyze personal interests through the library's borrowing history, but it involves important privacy and ethical issues and needs to be handled carefully. The following is a detailed analysis： --- ### **1. Technical feasibility** -**Data basis**: Library systems usually record the title of the borrowed book, the author, the classification number (such as Dewey decimal or Zhongtu classification), the borrowing time, etc. These data can reflect the reader's reading tendency. -**Analysis method**： -**Subject classification**: Statistics of high-frequency categories through the subject classification of books (such as literature, science and technology, and history). -**Keyword extraction**: Analyze high-frequency words in book titles or keywords (such as "programming", "psychology", "science fiction"). -**Time trend**: Combine the borrowing time to observe changes in interest (such as the recent concentrated borrowing of books in a certain field). -**Collaborative filtering**: Compare the borrowing records of similar readers and speculate on potential interests (group data support is required). --- ### **2. Privacy and legal restrictions** -**Personal Information Protection Law**: China's "Personal Information Protection Law" stipulates that borrowing records are sensitive personal information and may not be processed without the user's express consent. Libraries usually have no right to disclose or analyze personal borrowing history. -**Library Ethics**: The INTERNATIONALFLA (IFLA) "Declaration on Library Ethics" emphasizes the protection of user privacy and prohibits the use of borrowed data for non-service purposes. --- ### **3. Legal application scenarios** -**User independent authorization**: Individuals can request the library to provide their own borrowing records and analyze their interests by themselves (some libraries provide such services). -**Aggregated analysis**: The library analyzes the group data (such as popular book statistics) of **desensitization** for procurement or service optimization, but not for individuals. -**Academic research**: Subject to ethical review, researchers may be allowed to use anonymous data to study reading behavior patterns. --- ### **4. Alternative** If you cannot obtain borrowing data, you can consider： -**Public book reviews or social platforms**: Such as reading records shared by users on Douban and Goodreads. -**Questionnaire survey**: Directly ask about interests (pay attention to the design of the questionnaire to avoid inducement). --- ### **5. Risk warning** -**Risk of data abuse**: Even if the data has been desensitized, it is still possible to re-identify the individual in combination with other information. -**Possibility of misjudgment**: Borrowing records≠ true interests (such as borrowing books for school/work may not reflect hobbies). --- ###**Conclusion** It is technically feasible, but legal and ethical norms must be strictly observed. Unless expressly authorized by the user or completely anonymous aggregated data is used, no attempt should be made to analyze personal interests through the library system. It is recommended to give priority to information or legal channels that users actively disclose.