Autors: Prebreza, R. R., Gotseva, D. A., Nakov, O. N.
Title: Recommendation Systems Based on Textual Document Analysis
Keywords: Recommendation System , Data mining , Text mining , Customizing users , RAKE

Abstract: IN general, recommendation systems are defined as techniques used to predict an individual assessment that will provide an item or social entities. These items can be books, movies, restaurants, and things to which individuals have different preferences. These systems help users to decide on the appropriate items and facilitate the task of finding a favorite collection items. The aim of this project is to create a system of recommendation based on textual documents, exactly will create an application making the recommendation of the mentor and the committee automatically based on the proposal of the topic and documents that are in the archive database. The algorithms that we have used are Rake which used to extract the keyword through textual documents and Leveshtein distance algorithm. This algorithm used to derive the similarity between documents based on keyword extraction that have the textual documents.



    29th National Conference with International Participation (TELECOM), pp. 90-95, 2021, Bulgaria, DOI 10.1109/TELECOM53156.2021.9659605

    Вид: постер/презентация в национален форум с межд. уч., публикация в реферирано издание, индексирана в Scopus