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Industry standard frameworks are now widespread for labeling the high-level stages and granular actions of attacker and defender behavior in cyberspace. While these labels are used for atomic actions, and to some extent for sequences of…

Cryptography and Security · Computer Science 2023-07-21 Georgel Savin , Ammar Asseri , Josiah Dykstra , Jonathan Goohs , Anthony Melarano , William Casey

Clustering is widely used in unsupervised learning to find homogeneous groups of observations within a dataset. However, clustering mixed-type data remains a challenge, as few existing approaches are suited for this task. This study…

Machine Learning · Statistics 2025-11-26 Badih Ghattas , Alvaro Sanchez San-Benito

This paper comprehensively surveys the development of trajectory clustering. Considering the critical role of trajectory data mining in modern intelligent systems for surveillance security, abnormal behavior detection, crowd behavior…

Computer Vision and Pattern Recognition · Computer Science 2018-02-21 Jiang Bian , Dayong Tian , Yuanyan Tang , Dacheng Tao

Malware attacks have become significantly more frequent and sophisticated in recent years. Therefore, malware detection and classification are critical components of information security. Due to the large amount of malware samples…

Cryptography and Security · Computer Science 2024-05-07 Olha Jurečková , Martin Jureček , Mark Stamp

Online social interactions in multiplayer games can be supportive and positive or toxic and harmful; however, few methods can easily assess interpersonal interaction quality in games. We use behavioural traces to predict affiliation between…

Human-Computer Interaction · Computer Science 2020-03-10 Julian Frommel , Valentin Sagl , Ansgar E. Depping , Colby Johanson , Matthew K. Miller , Regan L. Mandryk

Cohort analysis is a pervasive activity in web analytics. One divides users into groups according to specific criteria and tracks their behavior over time. Despite its extensive use, academic circles do not discuss cohort analysis to…

Machine Learning · Computer Science 2021-06-15 Vladislav Zhuzhel , Rodrigo Rivera-Castro , Nina Kaploukhaya , Liliya Mironova , Alexey Zaytsev , Evgeny Burnaev

Heterogeneity has been a hot topic in recent educational literature. Several calls have been voiced to adopt methods that capture different patterns or subgroups within students behavior or functioning. Assuming that there is an average…

Methodology · Statistics 2023-06-13 Luca Scrucca , Mohammed Saqr , Sonsoles López-Pernas , Keefe Murphy

Using statistical learning methods to analyze stochastic simulation outputs can significantly enhance decision-making by uncovering relationships between different simulated systems and between a system's inputs and outputs. We focus on…

Methodology · Statistics 2026-05-28 Mohammadmahdi Ghasemloo , David J. Eckman

Individual behavioral engagement is an important indicator of active learning in collaborative settings, encompassing multidimensional behaviors mediated through various interaction modes. Little existing work has explored the use of…

Social and Information Networks · Computer Science 2023-12-15 Shihui Feng , Lixiang Yan , Linxuan Zhao , Roberto Martinez Maldonado , Dragan Gašević

The use of mobile phones has exploded over the past years,abundantly through the introduction of smartphones and the rapidly expanding use of mobile data. This has resulted in a spiraling problem of ensuring quality of service for users of…

Networking and Internet Architecture · Computer Science 2016-02-24 Eleni Rozaki

Mode clustering is a nonparametric method for clustering that defines clusters using the basins of attraction of a density estimator's modes. We provide several enhancements to mode clustering: (i) a soft variant of cluster assignment, (ii)…

Methodology · Statistics 2015-12-23 Yen-Chi Chen , Christopher R. Genovese , Larry Wasserman

In this paper, we propose ART1 neural network clustering algorithm to group users according to their Web access patterns. We compare the quality of clustering of our ART1 based clustering technique with that of the K-Means and SOM…

Other Computer Science · Computer Science 2012-05-10 C. Ramya , G. Kavitha , K. S. Shreedhara

In a standard cluster analysis, such as k-means, in addition to clusters locations and distances between them, it's important to know if they are connected or well separated from each other. The main focus of this paper is discovering the…

Machine Learning · Statistics 2017-05-22 Evgeny Bauman , Konstantin Bauman

This paper advocates the exploration of the full state of recorded real-time strategy (RTS) games, by human or robotic players, to discover how to reason about tactics and strategy. We present a dataset of StarCraft games encompassing the…

Artificial Intelligence · Computer Science 2012-11-20 Gabriel Synnaeve , Pierre Bessiere

Human mobility demonstrates a high degree of regularity, which facilitates the discovery of lifestyle profiles. Existing research has yet to fully utilize the regularities embedded in high-order features extracted from human mobility…

Machine Learning · Computer Science 2023-12-04 Yeshuo Shu , Gangcheng Zhang , Keyi Liu , Jintong Tang , Liyan Xu

In this paper, we introduce a method performing clustering of time-series on the basis of their trend (increasing, stagnating/decreasing, and seasonal behavior). The clustering is performed using $k$-means method on a selection of…

Signal Processing · Electrical Eng. & Systems 2020-11-25 Vincent Talbo , Mehdi Haddab , Derek Aubert , Redha Moulla

Among the various market structures under peer-to-peer energy sharing, one model based on cooperative game theory provides clear incentives for prosumers to collaboratively schedule their energy resources. The computational complexity of…

Computational Engineering, Finance, and Science · Computer Science 2020-08-03 Liyang Han , Thomas Morstyn , Constance Crozier , Malcolm McCulloch

Difficulty is one of the key drivers of player engagement and it is often one of the aspects that designers tweak most to optimise the player experience; operationalising it is, therefore, a crucial task for game development studios. A…

Artificial Intelligence · Computer Science 2025-03-20 Jeppe Theiss Kristensen , Paolo Burelli

Over the past decade humans have experienced exponential growth in the use of online resources, in particular social media and microblogging websites such as Facebook, Twitter, YouTube and also mobile applications such as WhatsApp, Line,…

Information Retrieval · Computer Science 2015-09-09 Rishabh Soni , K. James Mathai

The detection of online influence operations -- coordinated campaigns by malicious actors to spread narratives -- has traditionally depended on content analysis or network features. These approaches are increasingly brittle as generative…

Social and Information Networks · Computer Science 2026-02-04 Philipp J. Schneider , Lanqin Yuan , Marian-Andrei Rizoiu
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