Читать книгу Advanced Analytics and Deep Learning Models - Группа авторов - Страница 52

Chandramouli Das, Abhaya Kumar Sahoo* and Chittaranjan Pradhan

School of Computer Engineering, KIIT Deemed to be University, Odisha, India

Abstract

Multi-criteria recommender systems are such kind of models that are made to give a user-friendly environment to the user. These models are widely used in every sector of the world. Many leading companies are putting effort to make these multi-criteria recommender models effective by introducing new techniques and approaches. In the past, people used to done the recommendation manually. For example, if someone wants to buy something, then they used to ask other people who have bought that particular thing or people who has some knowledge on that thing. To take this process genuine, automatic, and more efficient, the concept of recommender system came. The first recommender system was based on single criteria. That is known as single-criteria recommender system. But in real-world scenario for recommendation, a model needs to look at more than one criterion. So, the multi-criteria recommender concept came in the picture. In this chapter, we will dig into various types of multi-criteria recommender systems. Here, we will see some innovative ideas, approaches, and methods, which are applied to a multi-criteria recommender system more efficient and effective. We will see how these new and innovative approaches give better result compared to the conventional recommender systems. Here, we have talked about so many different approaches of multi-criteria recommendation techniques done by various researchers around the globe. All these researches are done with the real-world datasets to solve the practical problems. We have also chosen five most likely research activities and explained in details how they have conducted their research and got a successful outcome. But before we dive into the hardcore details, we will see that how a recommender system was made. We talked about the various filtering techniques and the core working principles of a recommender system. At the end of the chapter, we have also discussed about the advantages and disadvantages of the recommender systems. Recommender system helps a business to grow higher and higher and also helps to analyze the risks. For these reasons, multi-criteria recommender systems are trending in the market and got high demand.

Keywords: Clustering, entertainment, mean absolute error, multi-criteria, recommender system