Abstract: The adoption of Integrated Library Systems (ILS) became prevalent in the 1980s and 1990s as libraries began or continued to automate their processes. These systems enabled library staff work, in many cases, more efficiently than in the past. However, these systems are restrictive and has thus undergone changes over the years, making processes more efficient. One area of improved capabilities is that of “search”, which in this paper, builds on integrating topic modeling as a new feature in modern integrated library systems. Users can now partake and explore new ways of resolving text classification and data exploration problems on a typical library management and recommender systems. This aims also at improving book search, browse and help in book-selection decision making, using machine learning tools as the major tweak to the traditional search. It is however hoped that further application of topic modeling will be sought and developed as its usage has continually grown in the past few years.
Keywords: Integrated Library System, Latent Dirichlet Allocation, Machine Learning, Searching, Topic Modeling.
Title: Topic Modeling Application to Library Management Systems: The Latent Dirichlet Allocation Approach
Author: Babafemi Richard Adebayo
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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