This report develops and demonstrates algorithms for representing and displaying similarity data using three established cognitive models. The rst representational model, multidimensional scaling, represents objects as points in a coordinate space so that similar objects lie near each other. The second representational model, the additive tree, represents objects as terminal nodes in a tree so ...

We examine two types of similarity network­ s each based on a distinct notion of rele­ vance. For both types of similarity network­ s we present an efficient inference algorith­ m that works under the assumption that ev­ ery event has a nonzero probability of oc­ currence. Another inference algorithm is de­ veloped for type 1 similarity networks that works under no restriction, albeit less effi...

Efficient indexing support is essential to allow content-based image and video databases using similaritybased retrieval to scale to large databases (tens of thousands up to millions of images). In this paper, we take an in depth look at this problem. One of the major difficulties in solving this problem is the high dimension (6-100) of the feature vectors that are used to represent objects. We...

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...

This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, mult...

 In this research, a tri-objective mathematical model is proposed for the Transportation-Location-Routing problem. The model considers a three-echelon supply chain and aims to minimize total costs, maximize the minimum reliability of the traveled routes and establish a well-balanced set of routes. In order to solve the proposed model, four metaheuristic algorithms, including Multi-Objective Gre...