Emerging Technologies for Education
6th International Symposium, SETE 2021, Zhuhai, China, November 11–12, 2021, Revised Selected Papers
Article
Stock trend prediction (STP) aims to predict price fluctuation, which is critical in financial trading. The existing STP approaches only use market data with the same granularity (e.g., as daily market data). ...
Chapter and Conference Paper
Participatory budgeting (PB) is a democratic process that allows voters to directly participate in the decision-making process regarding budget spending. The process typically involves presenting voters with a...
Chapter and Conference Paper
This paper studies the problem of maximizing a k-submodular function under a knapsack constraint. A k-submodular function is a generalization of submodular functions, which takes k disjoint subsets of elements as...
Chapter and Conference Paper
Collaborative Mobile Edge Computing (MEC) has emerged as a promising solution for low service delay in computation-intensive Internet of Things (IoT) applications. However, current approaches typically perform...
Article
Altitude, season, and slope aspect have significant impacts on bacterial variation in forest soils. However, it is currently unclear which factor has the greatest influence.
Chapter
Tsinghua Primary School takes the personalized diagnosis of students’ academic quality as the starting point, and is guided by education, and the data analysis of students’ physical health performance is not s...
Chapter and Conference Paper
Video saliency detection is intended to interpret the human visual system by modeling and predicting while observing a dynamic scene. This method is currently widely used in a variety of devices, including sur...
Chapter and Conference Paper
Data Diversification is a recently proposed method of data augmentation for Neural Machine Translation (NMT). While it attracts broad attention due to its effectiveness, the reason for its success is unclear. In ...
Article
VANET is an emerging area of wireless ad-hoc networks to contribute in the success of connected vehicles projects. The extremely changeable number of mobile nodes and high mobility are challenging issues. Furt...
Book and Conference Proceedings
6th International Symposium, SETE 2021, Zhuhai, China, November 11–12, 2021, Revised Selected Papers
Article
Chapter and Conference Paper
Knowledge graph completion (KGC) aims to predict missing information in a knowledge graph. Many existing embedding-based KGC models solve the Out-of-knowledge-graph (OOKG) entity problem (also known as zero-sh...
Chapter and Conference Paper
Nowadays, O2O commercial platforms are playing a crucial role in our daily purchases. However, some people are trying to manipulate the online market maliciously by opinion spamming, a kind of web fraud behavi...
Article
Determining topological relations has proved to be one of the most important operations on spatiotemporal data, which still merits further attention. In this paper, we propose a valid and efficient topological...
Article
A key requirement of the cloud platform is the reasonable deployment of its large-scale virtual machine infrastructure. The mapping relation between the virtual node and the physical node determines the specif...
Article
This paper proposes a goodness-of-fit test for checking the adequacy of parametric forms of the regression error density functions in linear errors-in-variables regression models. Instead of assuming the distr...
Article
The problem of modeling and operating spatiotemporal data has received a great deal of interest, due to its various applications in the real world such as GIS and sensor database. A wide range of work covering...
Chapter and Conference Paper
In relation classification, previous work focused on either whole sentence or key words, meeting problems when sentence contains noise or key words are extracted falsely. In this paper, we propose coarse and f...
Chapter and Conference Paper
Entity linking, bridging text and knowledge base, is a fundamental task in the field of information extraction. Most existing approaches highly depend on the structural features and statistics in the target kn...
Chapter and Conference Paper
Knowledge graph completion (KGC) aims at predicting missing information for knowledge graphs. Most methods rely on the structural information of entities in knowledge graphs (In-KG), thus they cannot handle KG...