[Purpose/significance] Paper literature acquisitioning is still one of the most important basic tasks of the current library. Faced with the uncertain needs of readers and the evaluation of book value, the urgent task of interviewing is to improve the efficiency of interviews under the premise of ensuring quality. The decision-driven book intelligent interview system aims to integrate the scientific resource interview mechanism with an efficient and intelligent way of thinking to improve the efficiency of interview work and the quality of collection resources, and to realize the intelligentization of library interview work. [Method/process] Based on the research and practice status of the intelligent interviews, and according to the school discipline construction needs, the publisher model, the reader behavior analysis, the reader recommendation and the book price, the business rules and the weight of decision-making were set, which allowing the system to intelligently screen paper documents. This paper used the intelligent interview system of Chongqing University Library as an example to analyze 3 models of book evaluation, publishing house and subject quality, author and subject quality, and optimized interview work. Process, and implement different strategies for new book subscription, book addition, reader recommendation and other business scenarios to optimize the interview workflow. [Result/conclusion] This paper argues that the book intelligent interview system is driven by readers' requirement and "key disciplines" construction decision-making. Under the support of artificial intelligence technology, the construction of paper literature resources will effectively improve efficiency and quality, and will definitely become the current interview. The main direction of model change.