Article
Business
Xiaotian Liu, Peter T. L. Popkowski Leszczyc
Summary: This study examines the reference price effect of historical price lists on ending prices. The findings support the range theory, showing that the maximum price on the price list positively influences the auction ending price, while the price range has a negative effect. The reference price effects are also influenced by the number of prices on the list and the type of product sold.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2023)
Article
Computer Science, Artificial Intelligence
Yanni Li, Hui Li, Zhi Wang, Bing Liu, Jiangtao Cui, Hang Fei
Summary: This paper proposes a fully online data stream clustering algorithm called ESA-Stream, which can dynamically learn parameters in a self-adaptive manner, speed up dimensionality reduction, and effectively and efficiently cluster data streams in an online and dynamic environment. Experimental results on a wide range of synthetic and real-world data streams show that ESA-Stream outperforms state-of-the-art baselines considerably in both effectiveness and efficiency.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Chemistry, Analytical
Peng Shan, Zhigang Li, Qiaoyun Wang, Zhonghai He, Shuyu Wang, Yuhui Zhao, Zhui Wu, Silong Peng
Summary: In this study, a novel standard-free model adaption method called VSSOM was proposed, utilizing self-organizing maps and variable selection strategy to achieve stable selection of feature subsets across different batches with superior and comparable prediction performance.
ANALYTICA CHIMICA ACTA
(2021)
Article
Management
Ningning Wang, Ting Zhang, Xiaowei Zhu, Peimiao Li
Summary: The study investigates how online and offline retailers should set prices considering the reference price effect, and their market competition behavior. The results show that when the reference price effect is low, offline retailers dominate the market, when it is high, online retailers do so, and when it is moderate, co-existence is possible.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2021)
Article
Automation & Control Systems
Dominik Olszewski
Summary: The study introduces an enhanced adaptive version of SOM that preserves input data structure and captures data scattering, which has been empirically proven to be superior to other data visualization techniques.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Mathematics
Kamil Khadiev, Nikita Savelyev, Mansur Ziatdinov, Denis Melnikov
Summary: This article introduces a new technique called walking tree for developing noisy tree data structures. By applying this technique, the authors present noisy Self-Balanced Binary Search Tree and noisy segment tree, and use these data structures in quantum algorithms to solve string problems. The article also demonstrates a quantum lower bound and shows quantum speed-up for the string-sorting problem.
Article
Business
Na Zhou, Jin Tian, Minqiang Li
Summary: The study introduces an incremental-input SOM algorithm for generating online recommendation models, demonstrating superior recommendation accuracy compared to existing online recommendation algorithms.
ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Soledad Delgado, Federico Moran, Jose Carlos San Jose, Daniel Burgos
Summary: Accurately analyzing user behavior in online learning environments is crucial for early student follow-up and support to improve performance. Utilizing a novel unsupervised clustering technique based on the Self-Organizing Map (SOM) model can provide precise insights into student clusters, leading to tailored support for their needs.
Article
Business
Eugene J. S. Won, Yun Kyung Oh, Joon Yeon Choeh
Summary: This study presents a method for deriving inter-brand similarities and analyzing market structures based on user-generated content and sales data. The results show a significant correlation between user-generated online content and sales data.
ASIA PACIFIC JOURNAL OF MARKETING AND LOGISTICS
(2023)
Article
Computer Science, Information Systems
Byungjoo Chae, Jinsun Park, Tae-Hyun Kim, Donghyeon Cho
Summary: Online learning is a method used to update deep networks with input data in order to improve potential performance. A new online learning algorithm is introduced in this research, utilizing multiple reference images for both RefSR and SISR networks, showing improved performance and robustness to different degradation kernels. Experimental results demonstrate the seamless applicability of this online learning method to existing RefSR and SISR models.
Article
Computer Science, Artificial Intelligence
Chao He, Ming Li, Congxuan Zhang, Hao Chen, Peilong Zhong, Zhengxiu Li, Junhua Li
Summary: This article proposes a self-organizing map approach for constrained multi-objective optimization problems. By using a two-population evolution strategy and utilizing self-organizing maps to discover population distribution structure, the proposed approach can efficiently converge the population to feasible regions.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Information Systems
Sheng Qi, Juan Zou, Shengxiang Yang, Yaochu Jin, Jinhua Zheng, Xu Yang
Summary: This paper proposes a Self-exploratory Competitive Swarm Optimization algorithm for Large-scale Multiobjective Optimization (SECSO), which enhances algorithm diversity and convergence performance by exploring neighboring space and learning from other particles. Compared with other large-scale evolutionary algorithms, SECSO shows outstanding performance on LSMOP problems.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Jie Chen, Shengxiang Yang, Conor Fahy, Zhu Wang, Yinan Guo, Yingke Chen
Summary: In this paper, an online sparse representation clustering (OSRC) method is proposed for data stream clustering. By introducing low-dimensional projection and l(2,1)-norm optimization technique, the proposed method can adaptively handle the noise and redundancy in high-dimensional data and exploit evolving subspace structures. Experimental results demonstrate that the proposed method outperforms state-of-the-art methods for data stream clustering.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Zhirong Shen, Guanglin Zhang
Summary: This paper investigates an online decision problem of when to buy and cancel a discount plan to minimize overall cost. The authors propose deterministic and randomized online algorithms and optimize them for different scenarios.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2022)
Article
Energy & Fuels
Na Xu, Wei Zhu, Ru Wang, Qiang Li, Zhiwei Wang, Robert B. Finkelman
Summary: Understanding the modes of occurrence of elements in coal is crucial for evaluating their environmental and health impacts and recovering critical elements from coal ash. This paper introduces the application of the self-organizing map algorithm in analyzing the modes of occurrence of elements in coal and compares it with the average linkage hierarchical clustering algorithm. The results show that the self-organizing map algorithm provides more consistent results with the geochemical nature and previous investigations.
INTERNATIONAL JOURNAL OF COAL GEOLOGY
(2023)
Article
Computer Science, Hardware & Architecture
Flavia Bonomo-Braberman, Nick Brettell, Andrea Munaro, Daniel Paulusma
Summary: This article discusses the convexity and mim-width of bipartite graphs, and it proves that for certain families of graphs 7-t, the 7-t-convex graphs can be solved in polynomial time for NP-complete problems. It also explores the bounded and unbounded mim-width of 7-t-convex graphs for different sets 7-t.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Keqin Li
Summary: In this paper, we propose a computation offloading strategy to satisfy all UEs served by an MEC and develop an efficient method to find such a strategy. By using Markov chains to characterize UE mobility and calculating the joint probability distribution of UE locations, we can obtain the average response time of UEs and predict the overall average response time of tasks. Additionally, we solve the power constrained MEC speed setting problem.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Correction
Computer Science, Hardware & Architecture
Peter L. Bartlett, Philip M. Long
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Philipp Czerner, Roland Guttenberg, Martin Helfrich, Javier Esparza
Summary: This paper presents a construction method that produces population protocols with a small number of states, while achieving near-optimal expected number of interactions, for deciding Presburger predicates.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Katharina T. Huber, Leo van Iersel, Remie Janssen, Mark Jones, Vincent Moulton, Yukihiro Murakami, Charles Semple
Summary: This paper investigates the relationship between undirected and directed phylogenetic networks, and provides corresponding algorithms. The study reveals that the directed phylogenetic network is unique under specific conditions. Additionally, an algorithm for directing undirected binary networks is described, applicable to certain classes of directed phylogenetic networks.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Francesco Betti Sorbelli, Alfredo Navarra, Lorenzo Palazzetti, Cristina M. Pinotti, Giuseppe Prencipe
Summary: This study discusses the deployment of IoT sensors in an area that needs to be monitored. Drones are used to collect data from the sensors, but they have energy and storage constraints. To maximize the overall reward from the collected data and ensure compliance with energy and storage limits, an optimization problem called Multiple-drone Data-collection Maximization Problem (MDMP) is proposed and solved using an Integer Linear Programming algorithm.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Carla Binucci, Emilio Di Giacomo, William J. Lenhart, Giuseppe Liotta, Fabrizio Montecchiani, Martin Nollenburg, Antonios Symvonis
Summary: In this study, we investigate the problem of representing a graph as a storyplan, which is a model for dynamic graph visualization. We prove the NP-completeness of this problem and propose two parameterized algorithms as solutions. We also demonstrate that partial 3-trees always admit a storyplan and can be computed in linear time. Additionally, we show that even if the vertex appearance order is given, the problem of choosing how to draw the frames remains NP-complete.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Hardware & Architecture
Leszek Gasieniec, Tomasz Jurdzinski, Ralf Klasing, Christos Levcopoulos, Andrzej Lingas, Jie Min, Tomasz Radzik
Summary: This passage describes the Bamboo Garden Trimming Problem and presents approximation algorithms for both Discrete BGT and Continuous BGT.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
