In this paper, we propose an Interactive Fuzzy Interval Reasoning (FIR) method by combining fuzzy logic with interval computing to better serve Web users in terms of effectiveness and flexibility. Web users may use convenient interval inputs for online shopping. In order to serve different customers based on their preferences, different personalized fuzzy partitions to meet different needs are ...

This paper introduces a new approach for decision support. It is characterized by a collaborative decision making process relying on the implicit sharing of preferences and experience between di erent individuals facing similar decision problems. A recommendation principle is described, based on fuzzy ltering methods de ned from individual fuzzy preference relations and fuzzy similarity relatio...

The investment of mutual funds which investors are often required evaluating the investment strategies according to their own subjective preferences in terms of numerical values from various criteria. This situation can be regarded as a fuzzy multiple criteria decision-making (MCDM) problem. The purpose of this study attempts to propose an alternative approach, fuzzy multiple criteria decision ...

Constraint satisfaction is a fundamental Artificial Intelligence technique for knowledge representation and inference. However, the formulation of a static constraint satisfaction problem (CSP) with hard, imperative constraints is insufficient to model many real problems. Fuzzy constraint satisfaction provides a more graded viewpoint. Priorities and preferences are placed on individual constrai...

The aim of this paper is to develop a linear programming technique for multidimensional analysis of preferences in multiattribute group decision making under fuzzy environments. Fuzziness is inherent in decision data and group decision making processes, and linguistic variables are well suited to assessing an alternative on qualitative attributes using fuzzy ratings. A crisp decision matrix can...

In this paper, we have introduced an agent based e-commerce system which recommends products to buyers as per their preferences. Initially, the agent collects the buyers’ preferences in fuzzy or linguistically defined terms and based on this, presents them an ordered set of products. After obtaining the buyers’ feedbacks when they actually come across the products, the seller’s agent interacts ...

Although recommender systems have been well studied, there are still two challenges in the development of a recommender system, particularly in real-world B2B e-services: 1) items or user profiles often present complicated tree structures in business applications, which cannot be handled by normal item similarity measures and 2) online users’ preferences are often vague and fuzzy, and cannot be...

Most important decisions in organizations are made by groups of managers or experts. Methods for aggregating preferences and reconciling differences are needed in case decision makers have different viewpoints. Human judgments, including preferences are often vague and cannot be estimated in exact numerical values. This paper proposes a new method under the linguistic framework for heterogeneou...