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Improving the Accuracy of Recommender Systems Through Annealing [chapter]

Shefali Arora, Shivani Goel
2017 Lecture Notes in Networks and Systems  
It is all because of her that I was able to delve into a new field and implement the aspects of my research work in a stipulated amount of time.  ...  Coordinator, for providing all the facilities and the right environment for learning. I would also like to thank my colleagues for extending all kind of help and cooperation during thesis.  ...  Collaborative filtering to find similar users in a food recommender [4] 4` Memory-based collaborative filtering techniques Model-based collaborative filtering techniques  Memory-based collaborative  ... 
doi:10.1007/978-981-10-3920-1_30 fatcat:4wgyghts3vb5tono6fghl3i5pu

Diagnostic test accuracy

Jared M. Campbell, Miloslav Klugar, Sandrine Ding, Dennis P. Carmody, Sasja J. Hakonsen, Yuri T. Jadotte, Sarahlouise White, Zachary Munn
2015 International Journal of Evidence-Based Healthcare  
Owing to demands for improvements in speed, cost, ease of performance, patient safety, and accuracy, new diagnostic tests are continuously developed, and there are often several tests available for the  ...  A B S T R A C T Systematic reviews are carried out to provide an answer to a clinical question based on all available evidence (published and unpublished), to critically appraise the quality of studies  ...  known as the true positive proportion), whereas specificity is the probability of a person without the condition of interest having a negative result (also known as the true negative proportion). 4  ... 
doi:10.1097/xeb.0000000000000061 pmid:26355602 fatcat:uyjjd7vvg5dnvjkuhtu7hfvm3e

A probabilistic model to resolve diversity–accuracy challenge of recommendation systems

Amin Javari, Mahdi Jalili
2014 Knowledge and Information Systems  
The proposed recommendation model consists of two models: one for maximization of the accuracy and the other one for specification of the recommendation list to tastes of users.  ...  Thus, it is an important feature of a recommender system to make it possible to adjust diversity and accuracy of the recommendations by tuning the model.  ...  Collaborative Filtering In recommendation systems based on memory-based CF, in order to recommend a list of potential items to a target user, first, the model produces predictions for ratings of the target  ... 
doi:10.1007/s10115-014-0779-2 fatcat:6xirkzhjuracrfl4ht3nqhhfqe

A New Similarity Measure Based on Simple Matching Coefficient for Improving the Accuracy of Collaborative Recommendations

Vijay Verma, Rajesh Kumar Aggarwal
2019 International Journal of Information Technology and Computer Science  
Neighborhood-based approaches are traditional techniques for collaborative recommendations and are very popular due to their simplicity and efficiency.  ...  Neighborhood-based recommender systems use numerous kinds of similarity measures for finding similar users or items.  ...  {10,15,20,25} Neighborhood-Size 200 320 400 A New Similarity Measure Based on Simple Matching Coefficient for Improving the Accuracy of Collaborative Recommendations  ... 
doi:10.5815/ijitcs.2019.06.05 fatcat:px3mnqs3irh4hbrww4c7tz2hni

Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering [article]

Minghao Zhao, Le Wu, Yile Liang, Lei Chen, Jian Zhang, Qilin Deng, Kai Wang, Xudong Shen, Tangjie Lv, Runze Wu
2022 arXiv   pre-print
Recent years have witnessed the great accuracy performance of graph-based Collaborative Filtering (CF) models for recommender systems.  ...  Finally, experimental results on three benchmark datasets show that our proposed method can improve novelty without sacrificing accuracy under various graph-based CF backbones.  ...  For example, Sun et al. proposed a framework for improving accuracy and diversity of recommendation by jointly training the model on the observed graph and sampled subgraphs under the Bayesian framework  ... 
arXiv:2204.12326v1 fatcat:srwl5igck5eozggtcmolttr67m

A Generic Top-N Recommendation Framework For Trading-off Accuracy, Novelty, and Coverage [article]

Zainab Zolaktaf, Reza Babanezhad, Rachel Pottinger
2018 arXiv   pre-print
Standard collaborative filtering approaches for top-N recommendation are biased toward popular items.  ...  As a result, they recommend items that users are likely aware of and under-represent long-tail items.  ...  Lakshmanan, and Tamara Munzner for their help and valuable discussions. We also thank the anonymous reviewers for their constructive feedback.  ... 
arXiv:1803.00146v1 fatcat:pidntp42kjbuhfccpzpmqij3qi

A New Similarity Measure Based on Gravitational Attraction for Improving the Accuracy of Collaborative Recommendations

Vijay Verma, Computer Engineering Department, National Institute of Technology, Kurukshetra, Haryana, India-136119, Rajesh Kumar Aggarwal
2020 International Journal of Intelligent Systems and Applications  
This article proposes a new similarity measure for neighborhoodbased collaborative recommender systems based on Newton's law of universal gravitation.  ...  Neighborhood-based algorithms are traditional approaches for collaborative recommendations and are very popular due to their simplicity and efficiency.  ...  New Similarity Measure Based on Gravitational Attraction for Improving the Accuracy of Collaborative Recommendations  ... 
doi:10.5815/ijisa.2020.02.05 fatcat:wxg2qt7kergtrfaaedvtiqxdhy

Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation

Marco Ferrario, Paolo Chiodini, Lloyd E Chambless, Giancarlo Cesana, Diego Vanuzzo, Salvatore Panico, Roberto Sega, Lorenza Pilotto, Luigi Palmieri, Simona Giampaoli
2005 International Journal of Epidemiology  
With an alternative method for recalibration better risk estimates were obtained, but a cohort study was needed to obtain a properly calibrated risk equation.  ...  The aims of this paper are to derive a 10-year coronary risk predictive equation for adult Italian men, and to assess its accuracy in comparison with the Framingham Heart Study (FHS) and PROCAM study equations  ...  Simply applying the PROCAM equation, recalibrated using crude estimates of population 10-year risk for persons at mean risk levels, was not sufficient to improve the risk estimation.  ... 
doi:10.1093/ije/dyh405 pmid:15659467 fatcat:xd6lwuihnnhs5b2sz4ndauquvm

Multinational Assessment of Accuracy of Equations for Predicting Risk of Kidney Failure

Navdeep Tangri, Morgan E. Grams, Andrew S. Levey, Josef Coresh, Lawrence J. Appel, Brad C. Astor, Gabriel Chodick, Allan J. Collins, Ognjenka Djurdjev, C. Raina Elley, Marie Evans, Amit X. Garg (+16 others)
2016 Journal of the American Medical Association (JAMA)  
Addition of a calibration factor that lowered the baseline risk by 32.9% at 2 years and 16.5% at 5 years improved the calibration in 12 of 15 and 10 of 13 non-North American cohorts at 2 and 5 years, respectively  ...  However, in some regions the addition of a calibration factor may be necessary. person-years in the Pima Indian cohort.  ...  Baseline risk was estimated for each cohort using Cox proportional hazards models, holding the variable coefficients constant and equal to the original risk equations regression coefficients but allowing  ... 
doi:10.1001/jama.2015.18202 pmid:26757465 pmcid:PMC4752167 fatcat:pu67345s7fcbzmkig2bzdohscq

Estimating Psychological Networks and their Accuracy: A Tutorial Paper [article]

Sacha Epskamp, Denny Borsboom, Eiko I. Fried
2017 arXiv   pre-print
We first introduce the current state-of-the-art of network estimation. Second, we provide a rationale why researchers should investigate the accuracy of psychological networks.  ...  and centrality estimates for different variables differ from each other.  ...  As such, for a certain level of α at the very least 2/α bootstrap samples are needed. It is recommended however to use more bootstrap samples to improve consistency of results.  ... 
arXiv:1604.08462v4 fatcat:e44cetql7vgonbjpfhpofxpgse

Improving the Accuracy and Transparency of Underwriting with AI to Transform the Life Insurance Industry

Marc Maier, Hayley Carlotto, Sara Saperstein, Freddie Sanchez, Sherriff Balogun, Sears Merritt
2020 The AI Magazine  
We combined one of the largest application data sets in the industry with a responsible artificial intelligence framework to develop a mortality model and life score.  ...  We present a consumer-facing tool that uses a state-of-the-art method for interpretable machine learning to offer transparency into the life score.  ...  We also give thanks to our many colleagues at MassMutual, Haven Life, and LifeScore Labs, and our external collaborators for their continued partnership.  ... 
doi:10.1609/aimag.v41i3.5320 fatcat:uyqo5xp4hrbdvljqr3rqxoc574

Evaluating Link Prediction Accuracy on Dynamic Networks with Added and Removed Edges [article]

Ruthwik R. Junuthula, Kevin S. Xu, Vijay K. Devabhaktuni
2016 arXiv   pre-print
Finally we propose a unified metric to characterize link prediction accuracy effectively using a single number.  ...  We provide several recommendations on evaluating dynamic link prediction accuracy, including separation into two categories of evaluation.  ...  Researchers often also calculate the log-likelihood of a baseline model, which is then used to measure relative improvement of a proposed model in terms of log-likelihood.  ... 
arXiv:1607.07330v1 fatcat:k726tp47dvaqviefbl6lzozjsy

Personalized Standard Deviations Improve the Baseline Estimation of Collaborative Filtering Recommendation

Zhenhua Tan, Liangliang He, Danke Wu, Qiuyun Chang, Bin Zhang
2020 Applied Sciences  
Baseline estimation is a critical component for latent factor-based collaborative filtering (CF) recommendations to obtain baseline predictions by evaluating global deviations for both users and items  ...  The results prove that the proposed baseline estimation model has better predictive accuracy than the classical model and is efficient in improving prediction performance for existing latent factor-based  ...  Thank Fernando Ortega Requena for inviting us to submit this manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app10144756 fatcat:zc7zuspryrfofg6meppfesnw6u

Accuracy and bias of experts' adjusted forecasts

Vera Shanshan Lin, Paul Goodwin, Haiyan Song
2014 Annals of Tourism Research  
Highlights  On average, Delphi-based judgmental adjustments made to statistical forecasts of tourism numbers improved accuracy.  Forecasts for the long-haul markets were more accurate than those for  ...  Abstract This study investigates whether experts' group-based judgmental adjustments to econometric forecasts of tourism demand improve the accuracy of the forecasts and whether the adjusted forecasts  ...  rate indexes for Hong Kong and i th origin country/region at time t, respectively (all exchange rates were calculated based on the local currencies against the US dollar).  ... 
doi:10.1016/j.annals.2014.06.005 fatcat:3o2it53fsza3hoprmnpn35xq6e

Hubris or humility? Accuracy issues for the next 50 years of travel demand modeling

David T. Hartgen
2013 Transportation  
Only a few studies of model accuracy have been performed, but they find that the likely inaccuracy in the 20-year forecast of major road projects is ±30 % at minimum, with some estimates as high as ±40  ...  The first, termed 'hubris', proposes a multi-decade effort to substantially improve model forecasting accuracy over time by monitoring performance and improving data, methods and understanding of travel  ...  The author of course remains wholly responsible for the views expressed herein.  ... 
doi:10.1007/s11116-013-9497-y fatcat:x6sfyiajzzbwvpav7ppzzbxz6u
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