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However, little work on recommendation has taken the noisy nature of implicit feedback into consideration. In this work, we explore the central theme of denoising implicit feedback for recommender training. ... In Proceedings of the international conference on web search and data mining. ACM, 485--494. Digital Library. Google …
WASHINGTON — The Biden-Harris administration's Department of the Interior-led Interagency Working Group on Mining Laws, Regulations, and Permitting (IWG) today released its MRIWG Report …
Clinical data mining of predictive models offers significant advantages for re-evaluating and leveraging large amounts of complex clinical real-world data and experimental comparison data for tasks such as risk stratification, diagnosis, classification, and survival prediction. However, its translational application is still limited. One …
This brief is intended for business leaders in CSR, corporate philanthropy, procurement, supply chain, human resources, and other functions at large-scale mining companies …
Mining GPS Data for Trajectory Recommendation Peifeng Yin1, Mao Ye2, Wang-Chien Lee1, and Zhenhui Li3 1 Department of Computer Science and Engineering, Pennsylvania State University 2 Pintrest, San Francisco Bay Area, CA 3 College of Information Science and Technology, Pennsylvania State University pzy102@cse.psu.edu, …
Recommendation Systems interpretability has attracted more attention because it can increase users’ confidence in the Recommendation Systems. Most of the existing explainable recommendation models consider the interpretability of the recommendation methods,...
Our mining monitoring and management software for Windows GPU rigs is the perfect solution for those who prefer to mine on their Windows machines. ASIC monitoring With ASIC Hub, you can monitor and manage your Antminer, Avalon, Whatsminer, Innosilicon, and other major ASIC brands with ease.
To truly shift to "sustainable mining," governments and companies must recognize the social impacts of mining, and enact laws and regulations that require community consultation throughout the life of a …
Mining and metals companies today must contend with various geopolitical risks, supply chain risks, and target-market risks, but many do so from a strong financial position. For their companies to thrive in this decade, mining CEOs must think holistically and establish a plan-ahead team, focusing on the factors associated with value creation.
We propose a novel safer medication recommendation model PIMNet, which can effectively reduce drug-drug interactions. • We model from the perspective of patient information mining, which provides a new idea for medication recommendation. • We conduct adequate experiments on the public dataset MIMIC-III, which demonstrate …
In the world of recommender systems, so-called content-based methods are an important approach that rely on the availability of detailed product or item descriptions to drive the recommendation process. For example, recommendations can be generated for a target user by selecting unseen products that are similar to the products that the target …
The matrix S is the evaluation basis of our proposed data mining and recommendation approach and the density of matrix S is an important factor that influences the recommendation performances. Inspired by this observation, we validate the relationship between prediction accuracy (in the form of MAE) with respect to the …
Interior today announced the dates of public listening sessions to develop recommendations for improving federal hardrock mining regulations, laws and permitting processes.
6. The environmental conditions in existing and new mining areas should be maintained and, if possible, improved. In underground mining, this will involve controlling drainage, acid mine water, refuse piles, dust, noise, and subsidence and in surface mining, maintaining the optimum environmental conditions for reclamation of the mined areas. 7.
With the development of E-commerce, more and more people have strong desire to buy goods on the online shopping platform. But they often need to spend more time searching for satisfactory goods because of the large amount of data. We propose a commodity recommendation model of online shopping based on data mining method …
In terms of solution knowledge mining, Sauer and Roth-Berghofer (2012) described an automated mining method for solutions to highly specific problems. Ruiz et al. (2013) proposed an approach for maintenance problem-solving with the CBR mechanism, and used the process to solve new problems based on the solutions of similar past …
Binbin Hu, Chuan Shi, Wayne Xin Zhao, and Philip S. Yu. 2018. Leveraging Meta-path Based Context for Top- N Recommendation with A Neural Co-Attention Model. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (London, United Kingdom) (KDD '18).
The DAO requires mining contractors, permit holders, and permittees to include biodiversity measures in their respective environmental work program, environmental protection and enhancement ...
The remarkable progress of machine learning has led to some state-of-the-art algorithms in personalized recommendation. Previous recommendation algorithms generally learn users' and items' representations based on a user-item rating matrix. However, these methods only consider a user's own preference, but ignore the influence of the user's …
We integrate the KG and the CF graph to mine the supervision signals of the data itself under the self-supervised learning mechanism, and use auxiliary signals to improve the exactitude and robustness of knowledge-aware recommendations. • We propose a general model, AMMCN, which constructs a attribute mining multi-view contrastive …
To ensure that our emerging clean energy system is not built on dirty mining, we must reform the rules of the road for mining and invest in creating a …
Recently, more and more mobile apps are employed in the marketing field with technical advances. Mobile marketing apps have become a prevalent way for enterprise marketing. Therefore, it has been an important and urgent problem to provide personalized and accurate recommendation in mobile marketing, with a large number …
Chalice Mining Limited analysts consensus, targets, ratings and recommendations | Australian S.E.: CHN | Australian S.E.
mining reform should assure that a reliable and sustainable supply of critical minerals can be provided both through environmentally and socially responsible mining and processing projects and other
After generations of inadequate consultation with Indigenous communities and other mining-impacted areas, the recommendations call for specific mechanisms …
Point-of-Interest (POI) recommendation has been an important research topic in data mining and the popularity of location-based social networks (LBSNs) has significantly contributed to POI recommendation. The existing POI recommendation models mostly adopt various explicit social relationships under geographical space. The …
sequential recommendation, hard negative mining, graph mining ∗Corresponding author. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation
Data mining makes use of various methodologies in statistics and different algorithms, like classification models, clustering, and regression models to exploit the insights which are present in the large set of data. ... The aim of recommender systems is to supply simply accessible, high-quality recommendations for the user community. Its …
Recommendations for process mining researchers and the research community. Despite process mining's great potential to help healthcare organizations understand how their processes are actually executed, its use in healthcare outside a research context is limited. Starting from this observation, a two-day international …
Describing novel mathematical concepts for recommendation engines, Realtime Data Mining: Self-Learning Techniques for Recommendation Engines features a sound mathematical framework unifying approaches based on control and learning theories, tensor factorization, and hierarchical methods.Furthermore, it presents promising results of …