Product recommendation systems are essential for enhancing customer experience, and integrating them with mobile apps is crucial improving usability fostering user engagement. This study proposes a hybrid approach that utilizes comparative facts from pairwise comparison data lists, association rules as the method to formulate system. The employs dataset New-Cars Database app, comprising 30,867 ...

Can we trust without any reliable truth information? Most trust architectures work in a similar way: a trustor makes some observations, rates the trustee, and makes recommendations to his friends. When he faces a new case, he checks his trust table and uses recommendations given by trustworthy friends to decide whether he will undertake a given action. But what if the observations that are used...

In this paper, we examine the application of electronic marketplaces, populated by buying and selling agents representing their human users, learning about potential business partners and making recommendations to their users. We propose a novel incentive mechanism to address the unfair rating problem arising when modeling the trustworthiness of selling agents relies on propagation of ratings p...

Ranking systems such as those in product review sites and recommender systems usually use ratings to rank favorite items based on both their quality and popularity. Since higher ranked items are more likely selected and yield more revenues for their owners, providers of unpopular and low quality items have strong incentives to strategically manipulate their ranking. This paper analyzes the adve...

The inherent weakness of the data on user ratings collected from web, such as sparsity and cold-start, has limited the data analysis capability and prediction accuracy in recommender systems (RS). To alleviate this problem, trust has been incorporated in collaborative filtering (CF) approaches with encouraging experimental results. In this paper, we propose a computational model for trust-based...

Current major P2P systems focus on PCs and do not provide services for the mobile environment. Compared to traditional P2P, characteristics of Mobile P2P include unreliable connections, limited bandwidth and constraints of mobile devices. In addition, nomadic users demand applications and services that are context-aware, personalised, secure, and trustworthy. Recommender systems are one of thes...

In e-commerce applications, the magnitude of products and the diversity of venders cause confusion and difficulty for the common consumer to choose the right product from a trustworthy vender. Although people have recognized the importance of feedback and reputation for the trustworthiness of individual venders and products, they still have difficulty when they have to make a shopping decision ...

Trust has been extensively studied in fields as varied as economics [13,17], business and marketing [8,24], politics, e-commerce [1,14,41], psychology [7,42,50], sociology [27], medicine, nursing [15], and computing science [10,11,19,39,40,44]. Whilst many definitions of trust have been proposed, none has been agreed upon. However, there have been some good efforts in inventorizing the differen...

This paper describes a trust model for multiagent recommender systems. A user’s request for a travel recommendation is decomposed by the system into subtasks, corresponding to travel services. Agents select tasks autonomously, and accomplish them using knowledge derived from previous solutions or with the help of other agents. Agents maintain local knowledge bases and, when requested to support...