scholarly journals Personalized Recommendations Based on Sentimental Interest Community Detection

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Jianxing Zheng ◽  
Yanjie Wang
Keyword(s):  
Recommender Systems ◽  
Community Detection ◽  
Experimental Results ◽  
User Profiles ◽  
Community Based ◽  
Proposed Model ◽  
Communities Of Interest ◽  
Relationship Of ◽  
Resonance Group ◽  
Accuracy Performance

Communities have become a popular platform of mining interests for recommender systems. The semantics of topics reflect users’ implicit interests. Sentiments on topics imply users’ sentimental tendency. People with common sentiments can form resonant communities of interest. In this paper, a resonant sentimental interest community-based recommendation model is proposed to improve the accuracy performance of recommender systems. First, we learn the weighted semantics vector and sentiment vector to model semantic and sentimental user profiles. Then, by combining semantic and sentimental factors, resonance relationship is computed to evaluate the resonance relationship of users. Finally, based on resonance relationships, resonant community is detected to discover a resonance group to make personalized recommendations. Experimental results show that the proposed model is more effective in finding semantics-related sentimental interests than traditional methods.

scholarly journals A Stochastic Damage Model for Bond Stress-Slip Relationship of Rebar-Concrete Interface under Monotonic Loading

Materials ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3151 ◽  
Author(s):  
Xiaoyong Lv ◽  
Zhiwu Yu ◽  
Zhi Shan ◽  
Ju Yuan
Keyword(s):  
Damage Model ◽  
Monotonic Loading ◽  
Bond Stress ◽  
Experimental Results ◽  
Stochastic Behavior ◽  
Spring Element ◽  
Proposed Model ◽  
Relationship Of ◽  
Stochastic Damage ◽  
Concrete Interface

The stochastic bond stress-slip behavior is an essential topic for the rebar-concrete interface. However, few theoretical models incorporating stochastic behavior in current literature can be traced. In this paper, a stochastic damage model based on micro-mechanical approach for bond stress-slip relationship of the interface under monotonic loading was proposed. In order to describe the mechanical behaviors of the rebar-concrete interface, a microscopic damage model was proposed. By introducing a micro-element consists of parallel spring element, friction element and a switch element, the model is formulated. In order to reflect the randomness of the bond stress-slip behavior contributed by the micro-fracture in the interface, a series of paralleled micro-elements are adopted with the failure threshold of individual spring element is set as a random variable. The expression of both mean and variance for the bond stress-slip relationship was derived based on statistical damage mechanics. Furthermore, by utilizing a search heuristic global optimization algorithm (i.e., a genetic algorithm), parameters of the proposed model are able to be identified from experimental results, which a lognormal distribution has adopted. The prediction was verified against experimental results, and it reveals that the proposed model is capable of capturing the random nature of the micro-structure and characterizing the stochastic behavior.

Recommender Systems Based on Resonance Relationship of Criteria With Choquet Operation

2020 ◽  
Vol 16 (4) ◽  
pp. 44-62
Author(s):  
Hiep Xuan Huynh ◽  
Le Hoang Son ◽  
Giap Nguyen Cu ◽  
Tri Minh Huynh ◽  
Huong Hoang Luong
Keyword(s):  
Decision Making ◽  
Recommender Systems ◽  
Recommender System ◽  
User Requirements ◽  
R Language ◽  
Improve Efficiency ◽  
Proposed Model ◽  
Reasonable Solution ◽  
Decision Making Model ◽  
Relationship Of

Recommender systems are becoming increasingly important in every aspect of life for the diverse needs of users. One of the main goals of the recommender system is to make decisions based on criteria. It is thus important to have a reasonable solution that is consistent with user requirements and characteristics of the stored data. This paper proposes a novel recommendation method based on the resonance relationship of user criteria with Choquet Operation for building a decision-making model. It has been evaluated on the multirecsys tool based on R language. Outputs from the proposed model are effective and reliable through the experiments. It can be applied in appropriate contexts to improve efficiency and minimize the limitations of the current recommender systems.

Connected-Tube MPP Model for Unsupervised 3D Fiber Detection

2020 ◽  
Vol 2020 (14) ◽  
pp. 305-1-305-6
Author(s):  
Tianyu Li ◽  
Camilo G. Aguilar ◽  
Ronald F. Agyei ◽  
Imad A. Hanhan ◽  
Michael D. Sangid ◽  
...  
Keyword(s):  
Composite Material ◽  
Point Process ◽  
Marked Point ◽  
Experimental Results ◽  
Marked Point Process ◽  
Fiber Reinforced Composite ◽  
Reinforced Composite ◽  
Proposed Model ◽  
Cylinder Model ◽  
Reinforced Composite Material

In this paper, we extend our previous 2D connected-tube marked point process (MPP) model to a 3D connected-tube MPP model for fiber detection. In the 3D case, a tube is represented by a cylinder model with two spherical areas at its ends. The spherical area is used to define connection priors that encourage connection of tubes that belong to the same fiber. Since each long fiber can be fitted by a series of connected short tubes, the proposed model is capable of detecting curved long tubes. We present experimental results on fiber-reinforced composite material images to show the performance of our method.

scholarly journals Evaluation of recent advances in recommender systems on Arabic content

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mehdi Srifi ◽  
Ahmed Oussous ◽  
Ayoub Ait Lahcen ◽  
Salma Mouline
Keyword(s):  
Recommender Systems ◽  
High Performance ◽  
Large Scale ◽  
State Of The Art ◽  
Experimental Results ◽  
Recent Advances ◽  
Research Gap ◽  
Text Preprocessing

AbstractVarious recommender systems (RSs) have been developed over recent years, and many of them have concentrated on English content. Thus, the majority of RSs from the literature were compared on English content. However, the research investigations about RSs when using contents in other languages such as Arabic are minimal. The researchers still neglect the field of Arabic RSs. Therefore, we aim through this study to fill this research gap by leveraging the benefit of recent advances in the English RSs field. Our main goal is to investigate recent RSs in an Arabic context. For that, we firstly selected five state-of-the-art RSs devoted originally to English content, and then we empirically evaluated their performance on Arabic content. As a result of this work, we first build four publicly available large-scale Arabic datasets for recommendation purposes. Second, various text preprocessing techniques have been provided for preparing the constructed datasets. Third, our investigation derived well-argued conclusions about the usage of modern RSs in the Arabic context. The experimental results proved that these systems ensure high performance when applied to Arabic content.

scholarly journals Diversity Balancing for Two-Stage Collaborative Filtering in Recommender Systems

2020 ◽  
Vol 10 (4) ◽  
pp. 1257 ◽  
Author(s):  
Liang Zhang ◽  
Quanshen Wei ◽  
Lei Zhang ◽  
Baojiao Wang ◽  
Wen-Hsien Ho
Keyword(s):  
Collaborative Filtering ◽  
Recommender Systems ◽  
Social Relationships ◽  
Two Stage ◽  
Proposed Model ◽  
The Social ◽  
Item List ◽  
Ranking Strategy ◽  
High Prediction ◽  
Optimization Mechanism

Conventional recommender systems are designed to achieve high prediction accuracy by recommending items expected to be the most relevant and interesting to users. Therefore, they tend to recommend only the most popular items. Studies agree that diversity of recommendations is as important as accuracy because it improves the customer experience by reducing monotony. However, increasing diversity reduces accuracy. Thus, a recommendation algorithm is needed to recommend less popular items while maintaining acceptable accuracy. This work proposes a two-stage collaborative filtering optimization mechanism that obtains a complete and diversified item list. The first stage of the model incorporates multiple interests to optimize neighbor selection. In addition to using conventional collaborative filtering to predict ratings by exploiting available ratings, the proposed model further considers the social relationships of the user. A novel ranking strategy is then used to rearrange the list of top-N items while maintaining accuracy by (1) rearranging the area controlled by the threshold and by (2) maximizing popularity while maintaining an acceptable reduction in accuracy. An extensive experimental evaluation performed in a real-world dataset confirmed that, for a given loss of accuracy, the proposed model achieves higher diversity compared to conventional approaches.

The Constitutive Model for High Temperature Flow Behavior of SiC/6168Al Composite

2015 ◽  
Vol 1089 ◽  
pp. 37-41
Author(s):  
Jiang Wang ◽  
Sheng Li Guo ◽  
Sheng Pu Liu ◽  
Cheng Liu ◽  
Qi Fei Zheng
Keyword(s):  
Constitutive Model ◽  
Hot Deformation ◽  
Flow Behavior ◽  
Type Equation ◽  
Strain Rate Range ◽  
Compression Tests ◽  
Stress Strain ◽  
Hollomon Parameter ◽  
Proposed Model ◽  
Relationship Of

The hot deformation behavior of SiC/6168Al composite was studied by means of hot compression tests in the temperature range of 300-450 °C and strain rate range of 0.01-10 s-1. The constitutive model was developed to predict the stress-strain curves of this composite during hot deformation. This model was established by considering the effect of the strain on material constants calculated by using the Zenter-Hollomon parameter in the hyperbolic Arrhenius-type equation. It was found that the relationship of n, α, Q, lnA and ε could be expressed by a five-order polynomial. The stress-strain curves obtained by this model showed a good agreement with experimental results. The proposed model can accurately describe the hot flow behavior of SiC/6168Al composite, and can be used to numerically analyze the hot forming processes.

Association of Hemoglobin A1C With TDP-43 Pathology in Community-Based Elders

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012025
Author(s):  
Shahram Oveisgharan ◽  
Ana W. Capuano ◽  
Sukriti Nag ◽  
Sonal Agrawal ◽  
Lisa L. Barnes ◽  
...  
Keyword(s):  
Severity Score ◽  
Hemoglobin A1c ◽  
Oldest Old ◽  
Brain Regions ◽  
Inverse Association ◽  
Community Based ◽  
Cytoplasmic Inclusions ◽  
The Mean ◽  
High Level ◽  
Relationship Of

Objective.We tested the hypothesis that an inverse association exists between diabetes mellitus (DM) and hemoglobin A1C (A1C) with Transactive response DNA binding protein 43 (TDP-43) levels in older adults.Methods.We leveraged antemortem and postmortem data of decedents from three community-based clinical-pathological studies. DM status, A1C levels, and medications for DM were documented annually. TDP-43 cytoplasmic inclusions, evaluated in 6 brain regions using immunohistochemistry, were used to obtain a semiquantitative TDP-43 score (0-5) in each region, and scores were averaged across regions to obtain a TDP-43 severity score. We used linear regressions to test the association of DM and A1C with the TDP-43 severity score.Results.On average, participants (n=817) were 90 years old at the time of death, three fourth were women, and one fourth had DM. The mean A1C was 6.0% (SD=0.6). TDP-43 was observed in 54% of participants, and the mean TDP-43 score was 0.7 (range 0-4.5). A higher level of A1C was associated with a lower TDP-43 score (estimate=-0.156, S.E.=0.060, p=0.009) while DM had a borderline inverse association with the TDP-43 score (estimate=-0.163, S.E.=0.087, p=0.060). The association of higher levels of A1C with lower TDP-43 scores persisted after further adjustment by Apolipoprotein ε4, vascular risk factors, stroke, and hypoglycemic medications. Exclusion of the oldest old participants did not change the results.Conclusion.Overall, the results suggest that a high level of A1C is associated with less TDP-43 proteinopathy in older persons while the relationship of DM with TDP-43 needs further study.

Discussion on Micro-Structure and Transport Properties of Carbon Micro-Coil

2011 ◽  
Vol 399-401 ◽  
pp. 573-576
Author(s):  
Fa Yu Wu ◽  
Yi Yong Wang ◽  
Wei Juan Li ◽  
Yan Wen Zhou ◽  
Jun Wei Zhang
Keyword(s):  
Transport Properties ◽  
Electrical Transport ◽  
Experimental Results ◽  
Helical Conformation ◽  
Micro Structure ◽  
Electrical Transport Properties ◽  
Relationship Of

The micro-structure, the thermal and electrical transport properties, and their corresponding relationship of carbon micro-coils were discussed, based on the experimental results. The disordered micro-structure and the helical conformation of carbon micro-coils were responsible for the characteristic of their transport properties.

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