Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics最新文献_第2页

Estimating Deflation Representing People Spreading in Stream Data 估计通货紧缩，代表在流数据中传播的人

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405992

Takuma Toyoshima, Masaki Endo, Takuo Kikuchi, Shigeyoshi Ohno, H. Ishikawa

引用次数: 0

Designing Dynamic and Personalized Nudges 设计动态和个性化的推动

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405975

Sandor Dalecke, Randi Karlsen

引用次数: 7

Measuring Online Advertising Viewability and Analyzing its Variability Across Different Dimensions 测量网络广告可见性并分析其在不同维度上的可变性

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405965

Marta Expósito-Ventura, José A. Ruipérez Valiente, J. Forné

{"title":"Measuring Online Advertising Viewability and Analyzing its Variability Across Different Dimensions","authors":"Marta Expósito-Ventura, José A. Ruipérez Valiente, J. Forné","doi":"10.1145/3405962.3405965","DOIUrl":"https://doi.org/10.1145/3405962.3405965","url":null,"abstract":"Many of the current online business base completely their revenue models in earnings from online advertisement. A problematic fact is that according to Google more than half of display ads are not being seen. The International Advertising Bureau (IAB) has defined a viewable impression as an impression that at least 50% of its pixels are rendered in the viewport during at least one continuous second. Although there is agreement on this definition for measuring viewable impressions in the industry, there is no systematic methodologies on how it should be implemented or the trustworthiness of these implementations. In fact, the Media Rating Council (MRC) announced that there are inconsistencies across multiple reports attempting to measure this metric. For this reason, we select a subset of implementations to track viewable impressions and we perform a case study by implementing them in a webpage registered in the worldwide ad-network ExoClick in order to see their results on different dimensions. Our results show that the Intersection Observer API is the implementation that detects more viewable impressions and that there are significant viewability differences depending on the banner location on the website. Finally, we also propose an ensemble viewability method that proves to be able to detect a higher number of viewable impressions.","PeriodicalId":247414,"journal":{"name":"Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129263858","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: 2

Scalable Machine Learning on High-Dimensional Vectors: From Data Series to Deep Network Embeddings 高维向量上的可扩展机器学习:从数据序列到深度网络嵌入

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405989

Karima Echihabi, Konstantinos Zoumpatianos, Themis Palpanas

{"title":"Scalable Machine Learning on High-Dimensional Vectors: From Data Series to Deep Network Embeddings","authors":"Karima Echihabi, Konstantinos Zoumpatianos, Themis Palpanas","doi":"10.1145/3405962.3405989","DOIUrl":"https://doi.org/10.1145/3405962.3405989","url":null,"abstract":"There is an increasingly pressing need, by several applications in diverse domains, for developing techniques able to analyze very large collections of static and streaming sequences (a.k.a. data series), predominantly in real-time. Examples of such applications come from Internet of Things installations, neuroscience, astrophysics, and a multitude of other scientific and application domains that need to apply machine learning techniques for knowledge extraction. It is not unusual for these applications, for which similarity search is a core operation, to involve numbers of data series in the order of hundreds of millions to billions, which are seldom analyzed in their full detail due to their sheer size. Such application requirements have driven the development of novel similarity search methods that can facilitate scalable analytics in this context. At the same time, a host of other methods have been developed for similarity search of high-dimensional vectors in general. All these methods are now becoming increasingly important, because of the growing popularity and size of sequence collections, as well as the growing use of high-dimensional vector representations of a large variety of objects (such as text, multimedia, images, audio and video recordings, graphs, database tables, and others) thanks to deep network embeddings. In this work, we review recent efforts in designing techniques for indexing and analyzing massive collections of data series, and argue that they are the methods of choice even for general high-dimensional vectors. Finally, we discuss the challenges and open research problems in this area.","PeriodicalId":247414,"journal":{"name":"Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128841816","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: 10

Sights, titles and tags: mining a worldwide photo database for sightseeing 景点，标题和标签:挖掘世界各地的照片数据库观光

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405987

A. Luberg, Jakob Pindis, T. Tammet

引用次数: 0

Design and Development of Modular Industrial Robot Kit (Merlyn TRN-1) for classroom training in STEM and ROBOTICS: Real Time Intelligent Training System 用于STEM和机器人课堂培训的模块化工业机器人套件(Merlyn TRN-1)的设计与开发:实时智能培训系统

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405972

Merlyn Elizabeth Varkey, Khurmi Yashpreet Singh, A. Garg

引用次数: 0

Directions and Speeds of Mouse Movements on a Website and Reading Patterns: A Web Usage Mining Case Study 网站上鼠标移动的方向和速度与阅读模式:一个网络使用挖掘案例研究

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405982

Ilan Kirsh

{"title":"Directions and Speeds of Mouse Movements on a Website and Reading Patterns: A Web Usage Mining Case Study","authors":"Ilan Kirsh","doi":"10.1145/3405962.3405982","DOIUrl":"https://doi.org/10.1145/3405962.3405982","url":null,"abstract":"Mouse activity is known as an important indicator of user attention and interest on a web page. Many modern commercial web analytics services record and report mouse activity of users on websites. The position of the mouse cursor on the screen is the main source of information, as studies show a correlation between the cursor position during mouse activity and the user's eye gaze. This study focuses on mouse movement directions and speeds, and what they indicate, rather than on the mouse cursor position. Statistical analysis of mouse movements on a technical-educational website, which was selected for this study, sheds light on several interesting patterns. For example, most mouse movements in the examined usage data are either approximately horizontal or approximately vertical, horizontal mouse movements are more frequent than vertical mouse movements, and horizontal movements to the left and to the right are not equivalent in terms of moving time and speed. As this study shows, these statistical findings are related to the reading patterns and behaviors of web users. Associating mouse movements with text reading may potentially highlight content that most users tend to skip, and therefore, might not interest the website audience, and content that many readers read more than once or slowly, meaning it is possibly unclear. This could be useful in locating issues in textual content, in websites in general, and especially in online learning and educational technology applications.","PeriodicalId":247414,"journal":{"name":"Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134629934","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

Rough Set & Riemannian Covariance Matrix Theory for Mining the Multidimensionality of Artificial Consciousness 挖掘人工意识多维度的粗糙集&黎曼协方差矩阵理论

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405974

Rory A. Lewis

引用次数: 1

Concept Drift Detection on Data Stream for Revising DBSCAN Cluster 修正DBSCAN聚类的数据流概念漂移检测

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405990

Yasushi Miyata, H. Ishikawa

引用次数: 1

A Method for Ranking Tourist Attractions based on Geo-tagged Photographs and Image Quality Assessment 基于地理标记照片和图像质量评价的旅游景点排序方法

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI: 10.1145/3405962.3405991

Jhih-Yu Lin, Shu-Mei Wen, Masaharu Hirota, Tetsu Araki, H. Ishikawa

引用次数: 1