Yunjun Gao – författare

Together for the ICWL 2020 Conference and SETE 2020 Symposium 39 full papers were accepted together with 31 short papers out of 233 submissions. The papers focus on the following subjects:  Semantic Web for E-Learning, through Learning

Analytics, Computer-Supported Collaborative Learning, Assessment, Pedagogical Issues, E-learning Platforms, and Tools, to Mobile Learning and much more.

The 14 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 72 submissions. They are organized in the topical sections named: traffic management, data science, and city analysis.

Incomplete data is part of life and almost all areas of scientific studies. Users tend to skip certain fields when they fill out online forms; participants choose to ignore sensitive questions on surveys; sensors fail, resulting in the loss of certain readings; publicly viewable satellite map services have missing data in many mobile applications; and in privacy-preserving applications, the data is incomplete deliberately in order to preserve the sensitivity of some attribute values.

Query processing is a fundamental problem in computer science, and is useful in a variety of applications. In this book, we mostly focus on the query processing over incomplete databases, which involves finding a set of qualified objects from a specified incomplete dataset in order to support a wide spectrum of real-life applications. We first elaborate the three general kinds of methods of handling incomplete data, including (i) discarding the data with missing values, (ii) imputation for the missing values, and (iii) just depending on the observed data values. For the third method type, we introduce the semantics of k-nearest neighbor (kNN) search, skyline query, and top-k dominating query on incomplete data, respectively. In terms of the three representative queries over incomplete data, we investigate some advanced techniques to process incomplete data queries, including indexing, pruning as well as crowdsourcing techniques.

The two-volume set LNCS 10569 and LNCS 10570 constitutes the proceedings of the 18th International Conference on Web Information Systems Engineering, WISE 2017, held in Puschino, Russia, in October 2017.

The 49 full papers and 24 short papers presented were carefully reviewed and selected from 195 submissions. The papers cover a wide range of topics such as microblog data analysis, social network data analysis, data mining, pattern mining, event detection, cloud computing, query processing, spatial and temporal data, graph theory, crowdsourcing and crowdsensing, web data model, language processing and web protocols, web-based applications, data storage and generator, security and privacy, sentiment analysis, and recommender systems.

The two-volume set LNCS 10569 and LNCS 10570 constitutes the proceedings of the 18th International Conference on Web Information Systems Engineering, WISE 2017, held in Puschino, Russia, in October 2017.

The 49 full papers and 24 short papers presented were carefully reviewed and selected from 195 submissions. The papers cover a wide range of topics such as microblog data analysis, social network data analysis, data mining, pattern mining, event detection, cloud computing, query processing, spatial and temporal data, graph theory, crowdsourcing and crowdsensing, web data model, language processing and web protocols, web-based applications, data storage and generator, security and privacy, sentiment analysis, and recommender systems.

This book analyzes unexpected preference query results for three problems: causality and responsibility problems, why-not and why questions, and why-few and why-many questions. Further, it refines preference queries and discusses how to modify the original preference query based on different objectives, in order to obtain satisfying results. This highly informative and carefully presented book provides valuable insights for researchers, postgraduates and practitioners with an interest in database usability.