J. Hamidzadeh
Faculty of Computer Engineering & Information Technology, Sadjad University of Technology, Mashhad, Iran.
[ 1 ] - IRDDS: Instance reduction based on Distance-based decision surface
In instance-based learning, a training set is given to a classifier for classifying new instances. In practice, not all information in the training set is useful for classifiers. Therefore, it is convenient to discard irrelevant instances from the training set. This process is known as instance reduction, which is an important task for classifiers since through this process the time for classif...
[ 2 ] - Ensemble-based Top-k Recommender System Considering Incomplete Data
Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user-interest (Top-k recommendation problem). Demanding sufficient ratings to make robust predictions and suggesting qualified recommendations are two si...
[ 3 ] - Design a Hybrid Recommender System Solving Cold-start Problem Using Clustering and Chaotic PSO Algorithm
One of the main challenges of increasing information in the new era, is to find information of interest in the mass of data. This important matter has been considered in the design of many sites that interact with users. Recommender systems have been considered to resolve this issue and have tried to help users to achieve their desired information; however, they face limitations. One of the mos...
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