Online Service for Express Movie Recommendations

Machine Learning, including Natural Language Processing algorithms, are implementing in the broader spectre of fields, among them, in the sphere of recommendation services. In their turn, they also are developing at fast pace. This work researches at which extent the application of Natural Language Processing algorithms is relevant in the context of the issue of the movie-recommendation services improvement. So far, there are quite significant number of such services, which performance is based on meta-information about movies like genre, director, actors participated, and description of the film. This paper will discover the online-service of movie recommendations, implementing, first of all, texts from users' reviews of the films they have watched. This work describe the development process of a client-server application, that would allow users to search among recommended movies by the key words. Besides, this paper considers existing competitive solutions and their disadvantages when compared to the proposed solution. In addition, there are explanation and motivation of choice of particular algorithms and technologies. The work contains 45 pages, 4 chapters, 25 pictures, 12 sources, 4 appendices. Keywords - movie recommendations, recommendation service, Natural Language Processing, client-server application.