A New Method for E‐Government Procurement Using Collaborative Filtering and Bayesian Approach

Abstract

Nowadays, as the Internet services increase faster than ever before, government systems are reinvented as E-government services. Therefore, government procurement sectors have to face challenges brought by the explosion of service information. This paper presents a novel method for E-government procurement (eGP) to search for the optimal procurement scheme (OPS). Item-based collaborative filtering and Bayesian approach are used to evaluate and select the candidate services to get the top-M recommendations such that the involved computation load can be alleviated. A trapezoidal fuzzy number similarity algorithm is applied to support the item-based collaborative filtering and Bayesian approach, since some of the services' attributes can be hardly expressed as certain and static values but only be easily represented as fuzzy values. A prototype system is built and validated with an illustrative example from eGP to confirm the feasibility of our approach.

Optimization of fuzzy similarity by genetic algorithm in user‐based collaborative filtering recommender systems

“…Zhang et al combine item-based collaborative filtering and a bayesian approach for selecting suitable services, represented through a trapezoidal fuzzy number (Zhang, Xi, et al, 2013).…”

“…Fuzzy inference‐based approaches.Nguyen and Duong propose model‐based collaborative filtering using a fuzzy neural network to learn the user's behaviours for video recommendation (Nguyen & Duong, 2015). Fuzzy Bayesian approaches.Zhang et al combine item‐based collaborative filtering and a bayesian approach for selecting suitable services, represented through a trapezoidal fuzzy number (Zhang, Xi, et al, 2013). Fuzzy association rules‐based approaches.Teng et al propose a Fuzzy Analytical Hierarchy Process (FAHP)‐based recommendation method by fusing a priori rule mining (Teng et al, 2016).…”

Fuzzy Tools in Recommender Systems: A Survey

“…Other approaches that also integrate fuzzy and bayesian concepts, have been proposed by Kant and Bharadwaj [59] and Zhang et al [153]. Table 8 presents a further analysis of these works.…”

A novel method for MCDM and evaluation of manufacturing services using collaborative filtering and IVIF theory

“…Zhang et al. 26 proposed a novel method using CF and a Bayesian approach for an optimal procurement scheme in which criteria are expressed as trapezoidal fuzzy numbers. However, they replaced CF’s similarity calculating method with a fuzzy number similarity algorithm.…”

“…Thus, Rodriguez et al 25 used linguistic values and a linguistic 2-tuple model to manage uncertain information caused by human cognitive processes. Zhang et al 26 proposed a novel method using CF and a Bayesian approach for an optimal procurement scheme in which criteria are expressed as trapezoidal fuzzy numbers. However, they replaced CF's similarity calculating method with a fuzzy number similarity algorithm.…”