A new confidence-based recommendation approach: Combining trust and certainty

Gohari, Faezeh Sadat; Aliee, Fereidoon Shams; Haghighi, Hassan

doi:10.1016/j.ins.2017.09.001

Cited by 50 publications

(25 citation statements)

References 35 publications

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“…Trust-based recommender systems are mainly a combination of a trust model and a method of collaborative filtering in order to take a hybrid approach to improve the performance of CF methods [18,26]. As stated in the introduction section, there are two main methods of recommendation based on trust, depending on the type of trust information, which could be explicit or implicit.…”

Section: Related Workmentioning

confidence: 99%

“…Various strategies have been designed to resolve these problems, one of the most important is the trust that has acquired lots of thought in recent years [15]. There are several investigations, which have reported that trust statements increase the quality of the recommendation in CF-based systems [14][15][16][17][18][19][20][21][22][23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

“…For example, it requires the users' effort to represent their statements of trust in others, so not all users necessarily provide explicit trust statements [28]. Moreover, some websites and applications do not have the ability to obtain the users' explicit trust in others, such as Movie Lens, which is why some studies have proposed methods to compute implicit trust instead [26,29].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Trust Computation Method Based on User Ratings to Improve the Recommendation

Nozari

Koohi

Mahmodi

2020

IJE

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Today, the trust has turned into one of the most beneficial solutions to improve recommender systems, especially in the collaborative filtering methods. However, trust statements suffer from a number of shortcomings, including the trust statements sparsity, users' inability to express explicit trust for other users in most of the existing applications. To overcome these problems, this work presents a method for computing implicit trust based on user ratings, in which four influential factors including Similarity, Confidence, Analogous Opinion, and Distance are utilized to achieve trust. For computing users' similarity, Person Correlation Coefficient measure was applied. Confidence was computed through users' common in rated items. To compute users' analogous opinions, their ratings were evaluated from three aspects of their satisfaction, dissatisfaction, and indifference about the items. Euclidean distance was employed on users ratings for computing the distance. Finally, the factors were combined to reach the implicit trust. Moreover, fuzzy c-means clustering was applied to initially partition similar users for enhancing the performance positively. Finally, two MovieLens datasets of 100K and 1M have been used to evaluate this approach, and results have shown that the approach significantly increases Accuracy, Precision and Recall, compared to some other existing methods.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Novel Trust Computation Method Based on User Ratings to Improve the Recommendation

Nozari

Koohi

Mahmodi

2020

IJE

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“…It is further defined as a derivative of the personality of the individual and perceived object reliability [25], and faith in others to provide accurate assessments based on the preferences of the active user. Global trust is the average opinion of the whole community about the credibility of the user [26,27], relying on others not to be used. On the other hand, being trustworthy means that you do not use others for lack of satisfaction [28].…”

Section: Literature Backgroundmentioning

confidence: 99%

Trust and Distress Prediction in Modal Shift Potential of Long-Distance Road Freight in Containers: Modeling Approach in Transport Services for Sustainability

et al. 2018

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Confidence in intermodal transport has not yet been defined. There are many different approaches to the concept of trust. However, the authors have integrated them with the paradigm shift in light of the challenges of sustainability. The objective of this article is to indicate the directions and criteria for that indicate the implementation of the paradigm shift, relative to the idea of sustainable transport. The auxiliary objective is to predict which countries in a given year will have the TRUST status, i.e., implement the paradigm shift, and which ones will not implement it (DISTRESS). The study used taxonometric techniques and built a model using General Discriminant Analysis. On these bases, the utility function was approximated, including the directions of implementation of the paradigm shift, depending on the scale of the environmental load of transport. Over the course of this research, an original and innovative econometric model was constructed, pointing to three variables which have the greatest impact on trust. Thanks to the cognitive value of the model, it is possible to identify individuals who deserve trust (i.e., it will implement the paradigm shift) with 93% probability. In the future, it is worth expanding the research by programing models for each country.

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“…Faith to others in providing accurate assessments due to the preferences of the active user. Global trust is the average opinion of the whole community about the credibility of the user [25]. Relying on others not to be used.…”

Section: Literature Backgroundmentioning

confidence: 99%

Trust and Distress Prediction in Modal Shift Potential of Long-Distance Road Freight in Containers: Modelling Approach in Transport Services for Sustainability

Szaruga¹,

Skąpska²,

Załoga³

et al. 2018

Preprint

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Confidence in intermodal transport has not yet been defined. There are many different approaches to the concept of trust. However, the authors embedded them in the light of the challenges of sustainability, linking with the shift paradigm. The objective of the article is to indicate the directions and criteria for the implementation of the shift paradigm, inscribed in the idea of sustainable transport. The auxiliary objective is to predict which countries in a given year will have the TRUST status, i.e. implement the shift paradigm, and which will not implement it (DISTRESS). The article uses taxonometric techniques and built a model using General Discriminant Analysis. On their basis, the utility function was approximated, including the directions of implementation of the shift paradigm depending on the scale of the environmental load of transport. In the course of the research, an original and innovative econometric model was constructed, pointing to three variables, which had the greatest impact on trust. Thanks to the cognitive value of the model, it is possible to identify individuals who deserve the trust, i.e. it will implement the shift paradigm, with 93% probability. In the future, it is worth expanding the research by models for each country.

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A new confidence-based recommendation approach: Combining trust and certainty

Cited by 50 publications

References 35 publications

A Novel Trust Computation Method Based on User Ratings to Improve the Recommendation

A Novel Trust Computation Method Based on User Ratings to Improve the Recommendation

Trust and Distress Prediction in Modal Shift Potential of Long-Distance Road Freight in Containers: Modeling Approach in Transport Services for Sustainability

Trust and Distress Prediction in Modal Shift Potential of Long-Distance Road Freight in Containers: Modelling Approach in Transport Services for Sustainability

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