Sharif Digital Repository

Recommender systems are in the center of network science, and they are becoming increasingly important in individual businesses for providing efficient, personalized services and products to users. Previous research in the field of recommendation systems focused on improving the precision of the system through designing more accurate recommendation lists. Recently, the community has been paying attention to diversity and novelty of recommendation lists as key characteristics of modern recommender systems. In many cases, novelty and precision do not go hand in hand, and the accuracy-novelty dilemma is one of the challenging problems in recommender systems, which needs efforts in making a... 

The prime shortcoming of Wireless Sensor Networks (WSNs) is their energy constraint. The main energy consumer in a sensor node is its radio transmitter. One of the most effective methods to reduce the data transmission rate is data prediction. By data prediction, the amount of transmitted data is reduced; which results in energy saving and the longevity of the network life. Environmental variations almost have similar effects on different sensor sources in a sensor device. So, considering the correlation between different sources reduces the noise impact and increases data prediction accuracy. In this paper, temporal and multi-source correlations are used, to reduce data transmission in...