2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW)最新文献_第2页

Distribution-Driven, Embedded Synthetic Data Generation System and Tool for RDBMS 分布驱动的嵌入式RDBMS合成数据生成系统和工具

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-25

Joseph W. Hu, Ivan T. Bowman, A. Nica, Anil K. Goel

引用次数: 0

Blockchain Enabled Distributed Data Management - A Vision 区块链支持分布式数据管理-一个愿景

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-39

Furqan Baig, Fusheng Wang

引用次数: 7

Predicting Online User Purchase Behavior Based on Browsing History 基于浏览历史的在线用户购买行为预测

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-13

Yunghui Chu, Hui-Kuo Yang, Wen-Chih Peng

{"title":"Predicting Online User Purchase Behavior Based on Browsing History","authors":"Yunghui Chu, Hui-Kuo Yang, Wen-Chih Peng","doi":"10.1109/ICDEW.2019.00-13","DOIUrl":"https://doi.org/10.1109/ICDEW.2019.00-13","url":null,"abstract":"Recently, people tend to purchase through websites. This change allows e-commerce sites to collect user behavior data from web logs. E-commerce marketing forces usually make use of such data to come up with subsequent promotional campaign to drive more traffic, and converting into paying customers. In this paper we consider a special kind of e-commerce companies which sell products with similar property and usually at a high price. Therefore, the recommendation becomes less important than prediction of items(if any) bought. We want to discover potential buyers and deliver ads or even coupons to them, expecting them to be real buyers. In this paper, we model the buying behaviors from clicking records with patterns extracted using feature engineering approach. Our solution was to model two kinds of browsing behaviors, namely hesitant and impulsive respectively. In the model, we define some interaction features from click-streams which uncover users' purchase intention with the product pages, how long the user stays on that page, and then build a model which can predict users' preference. Experimental results on a real dataset from an e-commerce company demonstrate the effectiveness of the proposed method. The approaches in our work can be used to model user purchasing intent and applied to e-commerce sites which sell high-end products.","PeriodicalId":186190,"journal":{"name":"2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121193056","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

AutoCache: Employing Machine Learning to Automate Caching in Distributed File Systems AutoCache:在分布式文件系统中使用机器学习自动缓存

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-21

H. Herodotou

引用次数: 12

Towards Auto-Scaling Existing Transactional Databases with Strong Consistency 实现现有事务性数据库的强一致性自动伸缩

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-26

M. Georgiou, Aristodemos Paphitis, Michael Sirivianos, H. Herodotou

引用次数: 4

Towards Distributed Multi-model Learning on Apache Spark for Model-Based Recommender 基于模型推荐的Apache Spark分布式多模型学习研究

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-12

Anas Alzogbi, Polina Koleva, G. Lausen

引用次数: 2

Towards self-managing cloud-scale computing platforms: Experiences and challenges 迈向自我管理的云规模计算平台:经验与挑战

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-24

Jingren Zhou

引用次数: 0

Recommendation of Indian Cuisine Recipes Based on Ingredients 基于食材的印度菜食谱推荐

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-28

Nilesh Nilesh, Madhu Kumari, Pritom Hazarika, Vishal Raman

引用次数: 11

A Group Recommendation Approach Based on Neural Network Collaborative Filtering 基于神经网络协同过滤的群组推荐方法

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-18

J. Du, Lin Li, Peng Gu, Qing Xie

{"title":"A Group Recommendation Approach Based on Neural Network Collaborative Filtering","authors":"J. Du, Lin Li, Peng Gu, Qing Xie","doi":"10.1109/ICDEW.2019.00-18","DOIUrl":"https://doi.org/10.1109/ICDEW.2019.00-18","url":null,"abstract":"At present, the most popular recommendation algorithms belong to the class of latent factor models(LFM). Compared with traditional user-based and item-based collaborative filtering methods, the latent factor model effectively improves recommendation accuracy. In recent years, deep neural networks have succeeded in many research fields, such as computer vision, speech recognition, and natural language processing. However, there are few studies combining recommendation systems and deep neural networks, especially for group recommendation. Some academic studies have adopted deep learning methods, but they mainly use it to process auxiliary information, such as acoustic features of sounds, and semantic analysis of texts, the inner product is still used to deal with latent features of users and items. In this paper, we first obtain the nonlinear interaction of latent feature vectors between users and projects through multi-layer perceptron(MLP), and use the combination of LFM and MLP to achieve collaborative filtering recommendation between users and items. Secondly, based on the individual's recommendation score, a fusion strategy based on Nash equilibrium is designed to ensure the average satisfaction of the group users. Our experiments are conducted on the Track 1 of KDD CUP 2012 public data set, taking the square root mean square error(RMSE) as the evaluation index. The experiment compares the traditional LFM optimization model, the MLP model and the LFM-MLP hybrid model in individual recommendation, and compares the strategy proposed in this paper with the traditional three single group strategies, the most pleasure, the average strategy and the least misery. The experimental results show that the proposed method can effectively improve the accuracy of group recommendation.","PeriodicalId":186190,"journal":{"name":"2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133656192","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

Technical Mechanics of a Trans-Border Waste Flow Tracking Solution Based on Blockchain Technology 基于区块链技术的跨境废物流跟踪解决方案的技术机制

2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW) Pub Date : 2019-04-08 DOI: 10.1109/ICDEW.2019.00-38

Dominik Schmelz, K. Pinter, S. Strobl, Lei Zhu, Phillip Niemeier, T. Grechenig

{"title":"Technical Mechanics of a Trans-Border Waste Flow Tracking Solution Based on Blockchain Technology","authors":"Dominik Schmelz, K. Pinter, S. Strobl, Lei Zhu, Phillip Niemeier, T. Grechenig","doi":"10.1109/ICDEW.2019.00-38","DOIUrl":"https://doi.org/10.1109/ICDEW.2019.00-38","url":null,"abstract":"When it comes to waste management and waste tracking, the main objectives are: prevent and reuse as much waste as possible. In the last decade, there has been a strong shift from the disposal of waste to recycling thereof. Within the EU, EU member states are required to establish waste prevention programs through the \"Waste Framework EU Directive\" which attempts to turn the EU into a recycling society. Similar endeavors also exist in other countries and regions. With globalization, the disposal of waste became a lucrative business case, often without transparency whether the waste has been disposed of properly and according to regulations or directives installed by each country. Waste flow management is the basis of sustainable waste prevention and recycling. Short-term solutions and financial profit accelerated malpractice in waste disposal and recycling. The currently used systems cannot track waste across borders in a transparent, but data-protected and tamper-proof way. Therefore, solutions to address these concerns have to be found and implemented. Blockchain enables new approaches, especially in ecosystems with distrust in every participating stakeholder, which is the case in waste flow tracking. We introduce and discuss a novel solution for waste tracking, on the basis of blockchain technology and smart contracts, that fulfills the aforementioned requirements.","PeriodicalId":186190,"journal":{"name":"2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129352291","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: 11