Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleMarch 2024
Discovering Players’ Problem-Solving Behavioral Characteristics in a Puzzle Game through Sequence Mining
LAK '24: Proceedings of the 14th Learning Analytics and Knowledge ConferenceMarch 2024, Pages 498–506https://doi.org/10.1145/3636555.3636907Digital games offer promising platforms for assessing student higher-order competencies such as problem-solving. However, processing and analyzing the large volume of interaction log data generated in these platforms to uncover meaningful behavioral ...
- research-articleJanuary 2023
The application of advertising logo color design for big data and visual communication technology
Journal of Computational Methods in Sciences and Engineering (JOCMSE), Volume 23, Issue 32023, Pages 1479–1490https://doi.org/10.3233/JCM-226700Color is one of the three major elements of print advertising, and different color combinations can trigger different emotional experiences of human beings. At present, the application of color in advertising in China is relatively mature, but it ...
- research-articleJuly 2022
Genetic algorithm cleaning in sequential data mining: analyzing solutions to parsons' puzzles
GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference CompanionJuly 2022, Pages 2330–2333https://doi.org/10.1145/3520304.3534025Sequence mining has been receiving increasing attention from the data science community as it helps reveal the underlying patterns in a given phenomenon. For instance, clustering sequences of "actions" taken by users provide understandable trajectories ...
- research-articleJuly 2021
A Framework for Generating Summaries from Temporal Personal Health Data
ACM Transactions on Computing for Healthcare (HEALTH), Volume 2, Issue 3Article No.: 21, Pages 1–43https://doi.org/10.1145/3448672Although it has become easier for individuals to track their personal health data (e.g., heart rate, step count, and nutrient intake data), there is still a wide chasm between the collection of data and the generation of meaningful summaries to help ...
- extended-abstractMarch 2021
Interpretability and Effectiveness of Machine Learning Methods for Sequence Mining in Various Domains
WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data MiningMarch 2021, Pages 1113–1114https://doi.org/10.1145/3437963.3441670There is a diverse variety of demographic data that can be analyzed with modern methods of data mining to achieve better results. On the one hand, the main chosen task is to compare different methods for the next event prediction and gender prediction, ...
-
- research-articleJanuary 2021
Exploring the Affordances of Sequence Mining in Educational Games
TEEM'20: Eighth International Conference on Technological Ecosystems for Enhancing MulticulturalityOctober 2020, Pages 648–654https://doi.org/10.1145/3434780.3436562Games have become one of the most popular mediums across cultures and ages and the use of educational games is growing. There is ample evidence that supports the benefits of using games for learning and assessment. However, we do not usually find games ...
- short-paperAugust 2020
Understanding Reading Behaviors of Middle School Students
L@S '20: Proceedings of the Seventh ACM Conference on Learning @ ScaleAugust 2020, Pages 385–388https://doi.org/10.1145/3386527.3405948Rich models of students' learning and problem-solving behaviors can support tailored interventions by instructors and scaffolding of complex learning activities. Our goal in this paper is to identify students' reading behaviors as they engage with ...
- research-articleAugust 2020
Efficient Mining of Outlying Sequence Patterns for Analyzing Outlierness of Sequence Data
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 14, Issue 5Article No.: 62, Pages 1–26https://doi.org/10.1145/3399671Recently, a lot of research work has been proposed in different domains to detect outliers and analyze the outlierness of outliers for relational data. However, while sequence data is ubiquitous in real life, analyzing the outlierness for sequence data ...
- short-paperJanuary 2020
Extracting Polarity Shifting Patterns from Any Corpus Based on Natural Annotation
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Volume 19, Issue 2Article No.: 23, Pages 1–16https://doi.org/10.1145/3345518In recent years, online sentiment texts are generated by users in various domains and in different languages. Binary polarity classification (positive or negative) on business sentiment texts can help both companies and customers to evaluate products or ...
- research-articleJanuary 2020
Hybridization of population-based ant colony optimization via data mining
Intelligent Data Analysis (INDA), Volume 24, Issue 22020, Pages 291–307https://doi.org/10.3233/IDA-184431We propose a hybrid application of Population Based Ant Colony Optimization that uses a data mining procedure to wisely initialize the pheromone entries. Hybridization of metaheuristics with data mining techniques has been studied by several ...
- research-articleMarch 2018
Discovery and temporal analysis of latent study patterns in MOOC interaction sequences
LAK '18: Proceedings of the 8th International Conference on Learning Analytics and KnowledgeMarch 2018, Pages 206–215https://doi.org/10.1145/3170358.3170388Capturing students' behavioral patterns through analysis of sequential interaction logs is an important task in educational data mining and could enable more effective and personalized support during the learning processes. This study aims at discovery ...
- research-articleFebruary 2018
Chronodes: Interactive Multifocus Exploration of Event Sequences
- Peter J. Polack Jr.,
- Shang-Tse Chen,
- Minsuk Kahng,
- Kaya De Barbaro,
- Rahul Basole,
- Moushumi Sharmin,
- Duen Horng Chau
ACM Transactions on Interactive Intelligent Systems (TIIS), Volume 8, Issue 1Article No.: 2, Pages 1–21https://doi.org/10.1145/3152888The advent of mobile health (mHealth) technologies challenges the capabilities of current visualizations, interactive tools, and algorithms. We present Chronodes, an interactive system that unifies data mining and human-centric visualization techniques ...
- research-articleNovember 2017
Detecting Multiple Periods and Periodic Patterns in Event Time Sequences
CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge ManagementNovember 2017, Pages 617–626https://doi.org/10.1145/3132847.3133027Periodicity is prevalent in physical world, and many events involve more than one periods, eg individual's mobility, tide pattern, and massive transportation utilization. Knowing the true periods of events can benefit a number of applications, such as ...
- research-articleAugust 2017
When is a Network a Network?: Multi-Order Graphical Model Selection in Pathways and Temporal Networks
KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data MiningAugust 2017, Pages 1037–1046https://doi.org/10.1145/3097983.3098145We introduce a framework for the modeling of sequential data capturing pathways of varying lengths observed in a network. Such data are important, e.g., when studying click streams in the Web, travel patterns in transportation systems, information ...
- research-articleMay 2017
Efficient and Versatile FPGA Acceleration of Support Counting for Stream Mining of Sequences and Frequent Itemsets
ACM Transactions on Reconfigurable Technology and Systems (TRETS), Volume 10, Issue 3Article No.: 21, Pages 1–25https://doi.org/10.1145/3027485Stream processing has become extremely popular for analyzing huge volumes of data for a variety of applications, including IoT, social networks, retail, and software logs analysis. Streams of data are produced continuously and are mined to extract ...
- research-articleApril 2017
Action prediction models for recommender systems based on collaborative filtering and sequence mining hybridization
SAC '17: Proceedings of the Symposium on Applied ComputingApril 2017, Pages 1655–1661https://doi.org/10.1145/3019612.3019759Many recommender systems collect online users' activity and infer from it users' preferences. They record user actions of various types (e.g. clicks, views), and predict unknown, possibly future, interactions between users and items, mostly using ...
- short-paperMarch 2017
Towards mining sequences and dispersion of rhetorical moves in student written texts
LAK '17: Proceedings of the Seventh International Learning Analytics & Knowledge ConferenceMarch 2017, Pages 228–232https://doi.org/10.1145/3027385.3027433There is an increasing interest in the analysis of both student's writing and the temporal aspects of learning data. The analysis of higher-level learning features in writing contexts requires analyses of data that could be characterised in terms of the ...
- research-articleApril 2016
Modeling User Consumption Sequences
WWW '16: Proceedings of the 25th International Conference on World Wide WebApril 2016, Pages 519–529https://doi.org/10.1145/2872427.2883024We study sequences of consumption in which the same item may be consumed multiple times. We identify two macroscopic behavior patterns of repeated consumptions. First, in a given user's lifetime, very few items live for a long time. Second, the last ...
- research-articleNovember 2015
Temporal Association Rules for Modelling Multimodal Social Signals
ICMI '15: Proceedings of the 2015 ACM on International Conference on Multimodal InteractionNovember 2015, Pages 575–579https://doi.org/10.1145/2818346.2823305In this paper, we present the first step of a methodology dedicated to deduce automatically sequences of signals expressed by humans during an interaction. The aim is to link interpersonal stances with arrangements of social signals such as modulations ...
- research-articleAugust 2015
Collective Spammer Detection in Evolving Multi-Relational Social Networks
KDD '15: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data MiningAugust 2015, Pages 1769–1778https://doi.org/10.1145/2783258.2788606Detecting unsolicited content and the spammers who create it is a long-standing challenge that affects all of us on a daily basis. The recent growth of richly-structured social networks has provided new challenges and opportunities in the spam detection ...