A social recommender mechanism for e-commerce: Combining similarity, trust, and relationship

Li, Yung-Ming; Wu, Chun; Lai, Cheng Yang

doi:10.1016/j.dss.2013.02.009

Cited by 206 publications

(102 citation statements)

References 46 publications

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“…Thus. Hypotheses 15,16,17,18 and 19 are rejected. Subjects were grouped into two groups based on their age namely young and old in order to facilitate statistical tests where many age groups that were used in the survey and did not have sufficient number of responses to perform the test.…”

Section: Sample and Data Collectionmentioning

confidence: 99%

“…Therefore, various studies where carried out in the literature to investigate the effect of trust on the adoption of new technology in different domain such as e-commerce [14][15][16][17][18][19] and e-government [20][21][22][23][24][25][26]. Furthermore, trust has become one of the most critical factors affecting the adoption and usage of cloud services.…”

Section: A Technology and Trustmentioning

confidence: 99%

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An Empirical Investigation on the Impact of Trust Mediated Determinants and Moderating Factors on the Adoption of Cloud Computing

Alharbi¹

2017

IJITCS

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Abstract-In a prior study we found out that trust is an effective factor in the acceptance and adoption of cloud computing using the UTAUT. However, various relationships from the original UTAUT were not confirmed in the extended model for cloud computing. Therefore, we present here a study aimed at investigating the mediation effect of trust on users' attitude toward the adoption of cloud computing using UTAUT. It is also aimed to examine the role of five moderating factors which are gender, age, education, managerial level and job domain on subjects' behavioral intention to use cloud computing services. Data were collected from 219 subjects in order to test the modified model and were analyzed using Partial Least Square (PLS) algorithm. Experimental results demonstrated that Performance Expectancy and Facilitating Conditions are strongly mediated by trust for the behavioral intention to adopt cloud computing. Statistical results, on the other hand, indicated that the majority of the moderating factors did not have a significant impact on the acceptance of cloud computing. The paper finally concludes with the limitations of current study and directions for future work.

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Section: Sample and Data Collectionmentioning

confidence: 99%

Section: A Technology and Trustmentioning

confidence: 99%

An Empirical Investigation on the Impact of Trust Mediated Determinants and Moderating Factors on the Adoption of Cloud Computing

Alharbi¹

2017

IJITCS

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“…Traditional recommender systems can be divided into three sub-categories: content-based, collaborative filtering based and hybrid ones [6], [11]. Content based recommender systems rely on the idea that users tend to like those items which are similar to the items they liked in the past.…”

Section: Related Workmentioning

confidence: 99%

“…Studies [10], [11], [8] suggested that user opinions are influenced by not only their own preferences but also their trusted friends. Social recommendation attracted a lot of attention in recent studies [6], [8], [12] and several e-commerce systems tried to leverage user social information to improve the quality of their recommender systems [11], [13].…”

Section: Introductionmentioning

confidence: 99%

dTrust: A Simple Deep Learning Approach for Social Recommendation

Dang

Ignat

2017

2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC)

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. dTrust: a simple deep learning approach for social recommendationQuang-Vinh Dang, Claudia-Lavinia IgnatTo cite this version: Abstract-Rating prediction is a key task of e-commerce recommendation mechanisms. Recent studies in social recommendation enhance the performance of rating predictors by taking advantage of user relationships. However, these prediction approaches mostly rely on user personal information which is a privacy threat.In this paper, we present dTrust, a simple social recommendation approach that avoids using user personal information. It relies uniquely on the topology of an anonymized trust-useritem network that combines user trust relations with user rating scores. This topology is fed into a deep feed-forward neural network. Experiments on real-world data sets showed that dTrust outperforms state-of-the-art in terms of Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) scores for both warmstart and cold-start problems.

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“…Trust can be notated by value and may change according to the time period. Complete willingness and interactions are based only on the trust level [14].…”

Section: N Social Trust Level Modelmentioning

confidence: 99%

Efficient Mining and Recommendation of Extensive Data Through Collaborative Filtering in E-Commerce: A Survey

Kumar¹

2018

IJET

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E-Commerce is the most widely used technique nowadays. Buying and selling goods on the Internet has been most admired and frequently utilized. The humongous growth of the content available on the internet has made laborious for users to search and utilize information for classifying the products. Recommendation system regarded as the best way to help the customers in buying the related products. (GRS) group recommender system aims at enhancing the customer's benefits for buying the products. This paper summarizes the fuzzy tree matching, modeling user preference dynamics, web page recommendation, uncertainty analysis for keywords, recommender system application, temporal topic model for friend recommendation, autocratic decision-making system based on (GRS),modeling user recommender, evaluating recommender system and enhancing (GRS).

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A social recommender mechanism for e-commerce: Combining similarity, trust, and relationship

Cited by 206 publications

References 46 publications

An Empirical Investigation on the Impact of Trust Mediated Determinants and Moderating Factors on the Adoption of Cloud Computing

An Empirical Investigation on the Impact of Trust Mediated Determinants and Moderating Factors on the Adoption of Cloud Computing

dTrust: A Simple Deep Learning Approach for Social Recommendation

Efficient Mining and Recommendation of Extensive Data Through Collaborative Filtering in E-Commerce: A Survey

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