recommender systems (rs) provide personalized recommendation according to user need by analyzing behavior of users and gathering their information. one of the algorithms used in recommender systems is user-based collaborative filtering (cf) method. the idea is that if users have similar preferences in the past, they will probably have similar preferences in the future. the important part of col...

Recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. User similarity measurement plays an important role in collaborative filtering based recommender systems. In order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...

recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. user similarity measurement plays an important role in collaborative filtering based recommender systems. in order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...

Memory-based collaborative filtering is the most popular approach to build recommender systems. Despite its success in many applications, it still suffers from several major limitations, including data sparsity. Sparse data affect the quality of the user similarity measurement and consequently the quality of the recommender system. In this paper, we propose a novel user similarity measure based...

The supply chains in the Electronics industry have gone through some major changes over the last decades. Today’s Electronics landscape is highly competitive, with short product lifecycles, and unpredictable demands. Many specialized players have appeared in the industry. There is a growing need for collaboration between the different parties in this industry, which can be supported by software...

The key focus of this paper is to introduce an approach to collaborative concept design which makes use of critical thinking styles and methods. It consists of four stages aimed to generate concept ideas, in response to identified needs, to explore them, to develop a set of solutions, and to finally choose a solution through critical examination of the solution set. Experimental findings and re...

This paper considers the problem of matrix completion, when some number of the columns are arbitrarily corrupted. It is well-known that standard algorithms for matrix completion can return arbitrarily poor results, if even a single column is corrupted. What can be done if a large number, or even a constant fraction of columns are corrupted? In this paper, we study this very problem, and develop...

This paper introduces a framework for carrier dynamic collaboration. In particular it proposes and analyzes dynamic collaborative mechanisms that are incentive compatible. The dynamic collaborative environment is characterized by a set of carriers that have a proprietary set of customers that generate a stream of random demands over time. The proposed collaborative mechanism is such that upon e...