The application of AI in librarianship opens up new horizons of possibilities, from automating and optimizing traditional library processes to personalizing services for users.
One of the most popular uses of neural networks in libraries is to automate the process of indexing and classifying books. Neural networks can be used to analyze the content of works and to automatically assign subject tags. This will speed up searching, making it easier to navigate through the library’s reading rooms. In addition, neural networks can be easily configured to automatically recognize and classify new books. Librarians will be able to update the catalog more quickly and offer visitors up-to-date literature.
Automatic translation is another application of neural networks in libraries. Even simple neural networks are adapted to automatically translate books into different languages. As a result, the library will be able to offer visitors works in different languages, thereby expanding its audience.
Automatically analyzing reading interests and preferences is also easier to do with neural networks. Simple algorithms will analyze the history of book lending and help to recommend to specific readers the literature they are interested in. Personalized selections will definitely improve the quality of service at the library.
Libraries that frequently hold professional events can benefit from using neural networks to automatically process and analyze audio and video materials. In this way, the institution can quickly publish analytics, reports, and press releases on the results of past events. In addition, AI technologies are suitable for creating automatic subtitles for the library’s video materials. By doing so, the institution will increase the accessibility of events for the hearing impaired and those who do not speak a particular language.
Another application of neural networks in libraries is automating the checkout process for books and other materials. For example, neural networks can help create voice and facial recognition systems that allow patrons to check out books without having to talk to librarians or use reader cards.
Text mining systems – determine the credibility of facts, arguments, and conclusions in a book or article. Their action is aimed at providing up-to-date and verified information from authoritative sources, which is especially important in the context of bibliographic services.
Neural networks in libraries are also used to create virtual assistants that can communicate with users, answer their questions, help them navigate library resources, and provide other services. For example, there are even ready-made chatbots for cultural institutions that can automate responses in social networks or conduct an online game. Such programs can be easily integrated into social networks and the library’s website, as well as into a mobile application or even into some kind of device installed in the institution.
Library collection optimization and data analysis. By analyzing the proposed parameters, the neural network can issue recommendations for updating the library collection and purchasing the necessary materials. AI will analyze the demand, the composition of collections, the frequency of certain requests. Thus, the library will be able to promptly offer readers exactly what they need.
In general, neural networks can easily be entrusted with analyzing large amounts of any data: monitoring information about library visits, assessing the effectiveness of processes, etc.
Neural networks in the library are also used to create virtual tours. This allows to attract more readers and make the library accessible for those who for one reason or another find it difficult to get to the institution. In addition, virtual tours can also provide additional information about the library, its history and collections.
Prevention of technical breakdowns. Neural networks can be configured to monitor the performance of library equipment and predict the need for maintenance. This prevents breakdowns and generally reduces repair costs. Such measures are especially relevant for libraries that serve as methodological and resource centers.
Another important task for libraries is to ensure the safety of their visitors and staff. Neural networks can help to create a video surveillance system that will automatically recognize faces and warn of possible threats. This will allow libraries to respond quickly to any incidents and ensure a high level of security for the facility and everyone present.