There exist two dominant strategies for group recommendations (Amer-Yahia et al. 2009; Berkovsky and Freyne 2010): The first approach creates a pseudo-user representing the group and then makes recommendations to that pseudo-user, whereas the second strategy computes a recommendation list for each group member and then …
DOI: 10.1016/J.CIE.2021.107313 Corpus ID: 234893118; Solution knowledge mining and recommendation for quality problem-solving @article{Xu2021SolutionKM, title={Solution knowledge mining and recommendation for quality problem-solving}, author={Zhaoguang Xu and Yanzhong Dang}, journal={Comput.
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 …
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 …
This paper presents the results in developing a course recommendation system that will select appropriate courses for each student studying a major in the following semesters based on his/her current academic performance. We have applied several techniques based on data mining and learning analytics to predict students' learning …
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 [email protected], …
This brief is intended for business leaders in CSR, corporate philanthropy, procurement, supply chain, human resources, and other functions at large-scale mining companies …
Attentive group recommendation. In SIGIR. Google Scholar [3] Da Cao, Liqiang Nie, Xiangnan He, Xiaochi Wei, Shunzhi Zhu, and Tat-Seng Chua. 2017. Embedding factorization models for jointly recommending items and user generated lists. ... Proceedings of the 13th International Conference on Web Search and Data Mining. …
Recommendation. Technologies that attempt to predict, prevent, mitigate, or treat environmental problems will be increasingly important to the economic viability of the mining industry. Improved environmental technologies related to mine closures present the greatest opportunity for increasing productivity and saving energy.
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 …
Sequential recommendation aims to predict the next interaction by mining users' evolving interest from their historical behaviors. Through comprehensive study, we argue that the evolving interest consists of dynamic interest and static interest, both of which are important for recommendation tasks. However, it is still a challenging task to …
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 …
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The abundance of information on online purchasing websites makes it challenging for customers to locate products that match their preferences. However, the cold-start problem arises when there isn't enough previous data, making it harder to make accurate recommendations for new customers or products. The enormous number of …
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 …
Dancelets Mining for Video Recommendation Based on Dance Styles Abstract: Dance is a unique and meaningful type of human expression, composed of abundant and various action elements. However, existing methods based on associated texts and spatial visual features have difficulty capturing the highly articulated motion …
Process mining techniques can help organizations to improve their operational processes. Organizations can benefit from process mining techniques in finding and amending the root causes of performance or compliance problems. Considering the volume of the data and the number of features captured by the information system of …
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 …
Abstract: Enabling effective cloud service recommendation and ranking model helps cloud users settle on brief choices when they are up against by an enormous number of choices. This helps to improve the cloud users', as well as the service providers', satisfaction levels. In this paper, parameter reputation-based algorithms are proposed to boost the service …
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 …
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 …
To this end, we propose a LATent sTructure mining method for multImodal reCommEndation, which we term LATTICE for brevity. To be specific, in the proposed LATTICE model, we devise a novel modality-aware structure learning layer, which learns item-item structures for each modality and aggregates multiple modalities to obtain …
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 …
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
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.
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 …
After generations of inadequate consultation with Indigenous communities and other mining-impacted areas, the recommendations call for specific mechanisms …
The DAO requires mining contractors, permit holders, and permittees to include biodiversity measures in their respective environmental work program, environmental protection and enhancement ...
The book recommendation helps overcome the information overhead problem and through this, the user can quickly get books according to need within the shortest span of time. This paper proposes a Book recommendation system for eLearning using collaborative filtering and sequential pattern mining to serve individual requirements.
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