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Proceedings of the 3rd International Conference on Machine Learning and Soft Computing最新文献

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Personalized POI recommendation based on check-in data and geographical-regional influence 基于签到数据和地理区域影响的个性化POI推荐
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 2019-01-25 DOI: 10.1145/3310986.3311034
Chuang Song, Junhao Wen, Shun Li
{"title":"Personalized POI recommendation based on check-in data and geographical-regional influence","authors":"Chuang Song, Junhao Wen, Shun Li","doi":"10.1145/3310986.3311034","DOIUrl":"https://doi.org/10.1145/3310986.3311034","url":null,"abstract":"Nowadays, many people like to share the places they visited to their friends in the location-based social networks (LBSNs). Therefore, LBSNs have accumulated large-scale user check-in data and the availability of these data enables many location-based services to users. As a location-based service, point-of-interests (POI) recommendation can provide services to people and promote merchants. Many researchers utilize user-based collaborative filtering and geographical influence for POI recommendation. However, existing studies have two limitations: (1) when modeling user-based CF, users' POI preferences are not fully considered; (2) when modeling geographical influence, geographical features have not been explored deeply. In this paper, we propose a POI recommendation approach by improved user-based CF and geographical-regional influence. Firstly, we construct the user-POI matrix by normalized check-in frequencies, which can effectively represent user preferences. Secondly, we find that each user's check-in POIs can be divided into several regions. Accordingly, we integrate geographical influence with the regional feature to produce recommendation. Finally, we utilize a unified framework to combine improved user-based CF with geographical-regional influence for POI recommendation. Our experimental results on real-world dataset show that the proposed approach outperforms the state-of-the-art POI recommendation methods substantially.","PeriodicalId":252781,"journal":{"name":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131538412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Classification of Grain Discoloration via Transfer Learning and Convolutional Neural Networks 基于迁移学习和卷积神经网络的谷物变色分类
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 2019-01-25 DOI: 10.1145/3310986.3310997
Nghia Duong-Trung, Luyl-Da Quach, Minh Nguyen, Chi-Ngon Nguyen
{"title":"Classification of Grain Discoloration via Transfer Learning and Convolutional Neural Networks","authors":"Nghia Duong-Trung, Luyl-Da Quach, Minh Nguyen, Chi-Ngon Nguyen","doi":"10.1145/3310986.3310997","DOIUrl":"https://doi.org/10.1145/3310986.3310997","url":null,"abstract":"Grain discoloration disease of rice is an emerging threat to rice harvest in Vietnam as well as all over the world and it acquires specific attention as it results in qualitative loss of harvested crop. An accurate classification is preliminary to any kind of intervention. Unfortunately, collecting enough grain discoloration data as well as building and training a machine learning model from scratch is next to impossible due to the lack of hardware infrastructure and finance support. It painfully restricts the needs of rapid solutions to deal with the disease. For this purpose, this paper exploits the idea of transfer learning which is the improvement of learning in a new prediction task through the transfer of knowledge from a related prediction task that has already been learned. By utilizing convolutional neural networks trained with our collected data, our experiment shows that the proposed idea performs perfectly and achieves the classification accuracy of 88.2% with the acceptable training time on a normal laptop.","PeriodicalId":252781,"journal":{"name":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115814450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
Optimizing Digital Coupon Assignment Using Constrained Reinforcement Learning 利用约束强化学习优化数字优惠券分配
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 2019-01-25 DOI: 10.1145/3310986.3311004
Xinlin Yao, Xianghua Lu
{"title":"Optimizing Digital Coupon Assignment Using Constrained Reinforcement Learning","authors":"Xinlin Yao, Xianghua Lu","doi":"10.1145/3310986.3311004","DOIUrl":"https://doi.org/10.1145/3310986.3311004","url":null,"abstract":"Coupon marketing is a traditional but effective way to retain customers and stimulate new purchases. Recently, digital coupons have been widely used in e-commerce and distributed to almost everyone. However, the decision on when and whom to issue the coupon is often based on managers' experience and calling for optimization and automation. Collaborated with a leading e-commerce platform, we propose an exploratory constrained reinforcement learning modeling to optimize digital coupon distribution policy under the constraint of maximum offering number. Our experimental results showed that the optimal policy could increase the cumulative total sales about 6% comparing to the original policy of the platform. This work enriches the applications of reinforcement learning in real-world business practices and provides useful implications for future study on constrained reinforcement learning.","PeriodicalId":252781,"journal":{"name":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116570526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A cellular automata approach to simulate the diffusion of antibiotic residues on the surface of a river 一种模拟抗生素残留在河流表面扩散的元胞自动机方法
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 2019-01-25 DOI: 10.1145/3310986.3311013
N. H. Nguyen, Khoa Duc Nguyen, L. Nguyen, Tri Quang Nguyen, H. Huynh
{"title":"A cellular automata approach to simulate the diffusion of antibiotic residues on the surface of a river","authors":"N. H. Nguyen, Khoa Duc Nguyen, L. Nguyen, Tri Quang Nguyen, H. Huynh","doi":"10.1145/3310986.3311013","DOIUrl":"https://doi.org/10.1145/3310986.3311013","url":null,"abstract":"Antibiotics play an important role in aquaculture. However, abuse will leave a high residue of high levels of antibiotic residues that can endanger the environment by spreading of water to neighboring ponds and lakes. Therefore, it is important to control the residues of antibiotics in the water environment, especially on the water surface. For that we must have a system to collect and monitor residues of antibiotics in the environment. This paper proposes a simulation model to track antibiotic residues along the river with aquaculture sites based on the cellular automata theory. The results are based on data on antibiotic residues collected in Hau River, O Mon district, Can Tho City.","PeriodicalId":252781,"journal":{"name":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123467960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fuzzy Neuro Approach to Water Management Systems 水管理系统的模糊神经方法
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 2019-01-25 DOI: 10.1145/3310986.3311026
Aditi Kambli, Stuti Modi
{"title":"Fuzzy Neuro Approach to Water Management Systems","authors":"Aditi Kambli, Stuti Modi","doi":"10.1145/3310986.3311026","DOIUrl":"https://doi.org/10.1145/3310986.3311026","url":null,"abstract":"This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes using two mostly widely used particular types of data driven models, namely recurrent neural networks (RNN) and fuzzy logic-based models.. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using RNN to find optimum reservoir level and predicting peak daily demands.","PeriodicalId":252781,"journal":{"name":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","volume":"4 41","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120926171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Smart Mobility Improvement: Classifying Commuter Satisfaction in Sydney, Australia 智能交通改进:澳大利亚悉尼通勤满意度分类
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 2019-01-25 DOI: 10.1145/3310986.3311021
The Danh Phan
{"title":"Smart Mobility Improvement: Classifying Commuter Satisfaction in Sydney, Australia","authors":"The Danh Phan","doi":"10.1145/3310986.3311021","DOIUrl":"https://doi.org/10.1145/3310986.3311021","url":null,"abstract":"This paper attempts to derive useful insights from commuter feedback data. It investigates transportation mode, commuting density and peak hours in Sydney, Australia. Machine Learning techniques are then applied to analyse traveler satisfaction to discover useful models for classification. Experiments demonstrate that each method has its competitive advantages over others, and no approach completely outperform other methods in terms of accuracy, performance, and interpretability. It is suggested that one could use Support Vector Machine to classify satisfied commuters, and/or utilize Neural Network to classify unsatisfied travelers.","PeriodicalId":252781,"journal":{"name":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123361257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A genetic algorithm for solving a multi-trip vehicle routing problem with time windows and simultaneous pick-up and delivery in a hospital complex 基于遗传算法的多行程车辆路径问题求解
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 2019-01-25 DOI: 10.1145/3310986.3311031
Saâdia Khoukhi, Othmane El Yaakoubi, Chakib Bojji, Y. Bensouda
{"title":"A genetic algorithm for solving a multi-trip vehicle routing problem with time windows and simultaneous pick-up and delivery in a hospital complex","authors":"Saâdia Khoukhi, Othmane El Yaakoubi, Chakib Bojji, Y. Bensouda","doi":"10.1145/3310986.3311031","DOIUrl":"https://doi.org/10.1145/3310986.3311031","url":null,"abstract":"This paper addresses the multi-trip vehicle routing problem with time windows and simultaneous pick and delivery, in which a set of hospitals have to be visited by a fleet of homogeneous vehicles. The objective is to minimize the total cost that includes the traveling cost and the fixed cost of using vehicles, without violating temporal and capacity constraints. As for the solving approach, a genetic algorithm based on route-first cluster-second approach and splitting procedure is introduced. Then crossover and mutation operations are deployed to ensure the exploration and the diversity of the population. The proposed approach is tested on a set of instances from the literature.","PeriodicalId":252781,"journal":{"name":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129225389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Application of Computer Vision and Deep Learning in Breast Cancer Assisted Diagnosis 计算机视觉与深度学习在乳腺癌辅助诊断中的应用
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 2019-01-25 DOI: 10.1145/3310986.3311010
Yu Gu, Yang Jiayao
{"title":"Application of Computer Vision and Deep Learning in Breast Cancer Assisted Diagnosis","authors":"Yu Gu, Yang Jiayao","doi":"10.1145/3310986.3311010","DOIUrl":"https://doi.org/10.1145/3310986.3311010","url":null,"abstract":"In the general process of breast cancer diagnosis, doctors mainly analyze and judge B-mode ultrasound images through vision, which depends heavily on doctors' operational experience and technical level. Artificial intelligence methods represented by machine learning algorithms have made rapid progress in recent years, especially natural image classification, target detection, semantics segmentation based on computer vision technology have been relatively mature, and have been widely used successfully in various fields. So as to improve the automation ability and reduce human errors, etc. By using artificial intelligence technology such as computer vision and in-depth learning, an automated method is established to diagnose breast cancer B-mode ultrasound images. This method can quickly strengthen the correct diagnostic rate of front-line medical staff and reduce the difference of operation level between urban and rural doctors. It has obvious medical needs and wide social significance.","PeriodicalId":252781,"journal":{"name":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132993506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing 第三届机器学习与软计算国际会议论文集
Proceedings of the 3rd International Conference on Machine Learning and Soft Computing Pub Date : 1900-01-01 DOI: 10.1145/3310986
{"title":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","authors":"","doi":"10.1145/3310986","DOIUrl":"https://doi.org/10.1145/3310986","url":null,"abstract":"","PeriodicalId":252781,"journal":{"name":"Proceedings of the 3rd International Conference on Machine Learning and Soft Computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127723971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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