Aggregation operators based recommender system of collaborative filtering in Apache Spark environment

Author: oleg gugunava
Keywords: Recommendation system, Aggregation operators, Spark, Collaborative filtering
Annotation:

In this master’s work there is represented aggregation operators based recommender system of collaborative filtering in Apache Spark environment. The data included in the system are of expert nature and the source of information is the expert and his knowledge. With technological advances it has become important to deal with big data. Demand-based recommendations have become an effective method of data processing and retrieval. As time goes by the data grows the more and consequently the demand for recommendation systems increases. The paper discusses the collaborative filtering method used by the OWA and UNINORM aggregation operator to construct a similarity model between users. The work can be considered as follows: 1) Study the collaborative filtering model and develop its hybrid model using aggregation operators. 2) Realization of recommendation system model (as algorithmic as well as software). 3) Demonstrate the results of the work of the algorithm based on private examples and compare them to the modular level of the system.