Since their origin in 1990's, recommender systems have changed the intelligence of both
human and web. Many research articles have been published in various domains of …

Context-aware processing is a research hotspot in the recommendation area, which
achieves better recommendation accuracy by considering more context information such as …

This paper proposes a multi-demand negotiation model that takes the effect of human users'
psychological characteristics into consideration. Specifically, in our model each negotiating …

Nowadays, the most common way to pass the time is to watch a movie. Using search
engines, the user must wade through a sea of information to find the intended information …

Web'in dinamik ve heterojen yapısı sebebiyle, kullanıcıların büyük miktardaki veriler
arasından tercih yapmaları giderek zorlaşmaktadır. Bu sebeple, kullanıcıların modellenmesi …

Recommender systems are an answer to information overload on the web. They filter and
present to customers, small subsets of items that they are most likely to be interested in …

Recommending appropriate items to users is crucial in many e-commerce platforms. One
common approach consists in selecting the N most relevant items for each user. To achieve …

The recommender system is an efficient tool for online application, which exploits historical
user rating on item to make recommendations on items to users. This paper aims to enhance …

Collaborative filtering methods are widely accepted and used for item recommendation in
various applications and domains. Their simplicity and ability to provide recommendations …

One of the major practical challenges in recommendation systems is to study user-item
interactions(explicit or implicit) and precisely identify present preferences of users. But …