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Keyword: Recommender System
A Fuzzy-Based Approach and Adaptive Genetic Algorithm in Multi-Criteria Recommender Systems
Recommender Systems (RSs) are termed as web-based applications that make use of filtering methods and several machine learning algorithms to suggest relevant user objects. It can be said that some techniques are usually adopted or trained to develop these systems that generate lists of suitable recommendations. Conventionally, RS uses a single rating approach to preference…
Read More The Design of a Hybrid Model-Based Journal Recommendation System
There is currently an overload of information on the internet, and this makes information search a challenging task. Researchers spend a lot of man-hour searching for journals related to their areas of research interest that can publish their research output on time. In, this study, a recommender system that can assist researchers access relevant journals…
Read More Tolerance of Characteristics and Attributes in Developing Student’s Academic Achievements
The purpose of this research is to study the relevance of factors for the analysis of the effectiveness of suitable educational institutions that illustrate the significance of the characteristics and attributes of the student’s academic achievements and to identify the acceptance and tolerance of each attribute, which supports lifelong learning. The data used in this…
Read More Efficient Tensor Strategy for Recommendation
The era of big data has witnessed the explosion of tensor datasets, and large scale Probabilistic Tensor Factorization (PTF) analysis is important to accommodate such increasing trend of data. Sparsity, and Cold-Start are some of the inherent problems of recommender systems in the era of big data. This paper proposes a novel Sentiment-Based Probabilistic Tensor…
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