• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 247 matches

• 2025
• 
  D. Sudha, M. Krishnamurthy:
  Recommendation system for frequent item sets using multi-objective chaotic optimization with convolutional BiLSTM model. Appl. Intell. 55(7): 636 (2025)
• 
  Zengyou He, Xiaolei Li, Lianyu Hu, Mudi Jiang, Yan Liu:
  Community structure testing by counting frequent common neighbor sets. Inf. Sci. 691: 121649 (2025)
• 
  Youness Manzali, Khalidou Abdoulaye Barry, Flouchi Rachid, Youssef Balouki, Mohamed Elfar:
  An innovative clustering approach utilizing frequent item sets. Multim. Tools Appl. 84(10): 7835-7861 (2025)
• 2024
• 
  B. Sivaiah, R. Rajeswara Rao:
  A node sets based fast and scalable frequent itemset algorithm for mining big data using map reduce paradigm. Int. J. Data Min. Model. Manag. 16(3): 326-343 (2024)
• 
  Christian Maier, Jens Mattke, Katharina Pflügner, Tim Weitzel:
  Corrigendum to "Smartphone use while driving: A fuzzy-set qualitative comparative analysis of personality profiles influencing frequent high-risk smartphone use while driving in Germany" [International Journal of Information Management 55 (2020) 102207, ISSN 0268-4012]. Int. J. Inf. Manag. 74: 102656 (2024)
• 
  Deng Fan, Jiabin Wang, Lv Sheng:
  Optimization of frequent item set mining parallelization algorithm based on spark platform. Discov. Comput. 27(1): 38 (2024)
• 
  Hai Van Duong, Tin Chi Truong, Bac Le, Philippe Fournier-Viger:
  CG-FHAUI: an efficient algorithm for simultaneously mining succinct pattern sets of frequent high average utility itemsets. Knowl. Inf. Syst. 66(9): 5239-5280 (2024)
• 
  Akshit Sharma, Sam Reinher, Dinesh Mehta, Bo Wu:
  FLEXIS: FLEXible Frequent Subgraph Mining using Maximal Independent Sets. CoRR abs/2404.01585 (2024)
• 
  Xuan Li, Tingyi Ruan, Yankaiqi Li, Quanchao Lu, Xiaoxuan Sun:
  A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets. CoRR abs/2412.19420 (2024)
• 2023
• 
  Pamalla Veena, Sreepada Tarun, Rage Uday Kiran, Minh-Son Dao, Koji Zettsu, Yutaka Watanobe, Ji Zhang:
  Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set Complements. IEEE Access 11: 118676-118688 (2023)
• 
  Haonan Wu, Ruisheng Ran, Shunshun Peng, Mengmeng Yang, Taolin Guo:
  Mining frequent items from high-dimensional set-valued data under local differential privacy protection. Expert Syst. Appl. 234: 121105 (2023)
• 
  David R. Bickel:
  Maximum entropy derived and generalized under idempotent probability to address Bayes-frequentist uncertainty and model revision uncertainty: An information-theoretic semantics for possibility theory. Fuzzy Sets Syst. 453: 192-212 (2023)
• 
  Ambily Balaram, Nedunchezhian Raju:
  An effective reference-point-set (RPS) based bi-directional frequent itemset generation. Int. Arab J. Inf. Technol. 20(6): 890-898 (2023)
• 
  Changxiao Shao, Shian Yuan, Min Chai, Tai Jin, Kun Luo:
  A generalized variational level set method without frequent reinitialization for simulations of gas-liquid flows. J. Comput. Phys. 495: 112558 (2023)
• 
  Supriya Gupta, Aakanksha Sharaff, Naresh Kumar Nagwani:
  Frequent item-set mining and clustering based ranked biomedical text summarization. J. Supercomput. 79(1): 139-159 (2023)
• 
  Qingxiang Zhong, Xuan Luo, Jinquan Liu:
  Hydropower Signal Detection Via Knowledge Graph Enhaced by Frequent Term Sets. DSDE 2023: 32-36
• 2022
• 
  Ali Jazayeri, Christopher C. Yang:
  Frequent Subgraph Mining Algorithms in Static and Temporal Graph-Transaction Settings: A Survey. IEEE Trans. Big Data 8(6): 1443-1462 (2022)
• 
  Nataliya Boyko, Oleksandr Tkachyk:
  Model for Finding Frequent Sets in FP-growth for Multimodal Data. CMIS 2022: 126-143
• 
  Yifeng Hu, Tie Qiu, Jiancheng Chi, Xuan Yang, Zimu Wang, Wenguang Li:
  Traffic Data Scheduling of Frequent Application Sets for Task Offloading in Multi-access Edge Computing. ICC 2022: 1605-1610
• 2021
• 
  Ahmed Alia, Adel Taweel:
  Enhanced Binary Cuckoo Search With Frequent Values and Rough Set Theory for Feature Selection. IEEE Access 9: 119430-119453 (2021)
• 
  Piotr Nowakowski, Piotr Zórawski, Krzysztof Cabaj, Wojciech Mazurczyk:
  Detecting Network Covert Channels using Machine Learning, Data Mining and Hierarchical Organisation of Frequent Sets. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl. 12(1): 20-43 (2021)
• 
  Hanan A. Hosni Mahmoud, Hanan Abdullah Mengash:
  Machine Translation Utilizing the Frequent-Item Set Concept. Sensors 21(4): 1493 (2021)
• 
  Elias Aboutanios, Vidhyasaharan Sethu, Eliathamby Ambikairajah, David S. Taubman, Julien Epps:
  Teaching Signal Processing Through Frequent and Diverse Design: A Pedagogical Approach. IEEE Signal Process. Mag. 38(3): 133-143 (2021)
• 
  Jakub Peschel, Michal Batko, Jakub Valcík, Jan Sedmidubský, Pavel Zezula:
  FIMSIM: Discovering Communities by Frequent Item-Set Mining and Similarity Search. SISAP 2021: 372-383
• 
  Hang Fu, Wei Yang, Liusheng Huang:
  Private Frequent Itemset Mining in the Local Setting. WASA (2) 2021: 338-350
• 
  Anwesha Law, Ashish Ghosh:
  Improved Multi-label Classification with Frequent Label-set Mining and Association. CoRR abs/2109.10797 (2021)
• 2020
• 
  Wenyu Cao, Qiuyan Zhong, Haifeng Li, Shuyuan Liang:
  A Novel Approach for Associative Classification Based on Information Entropy of Frequent Attribute Set. IEEE Access 8: 140181-140193 (2020)
• 
  Muhammad Yasir, Muhammad Asif Habib, Muhammad Ashraf, Shahzad Sarwar, Muhammad Umar Chaudhry, Hamayoun Shahwani, Mudassar Ahmad, Chaudhry Muhammad Nadeem Faisal:
  D-GENE: Deferring the GENEration of Power Sets for Discovering Frequent Itemsets in Sparse Big Data. IEEE Access 8: 27375-27392 (2020)
• 
  Jerry Lonlac, Engelbert Mephu Nguifo:
  A novel algorithm for searching frequent gradual patterns from an ordered data set. Intell. Data Anal. 24(5): 1029-1042 (2020)
• 
  Christian Maier, Jens Mattke, Katharina Pflügner, Tim Weitzel:
  Smartphone use while driving: A fuzzy-set qualitative comparative analysis of personality profiles influencing frequent high-risk smartphone use while driving in Germany. Int. J. Inf. Manag. 55: 102207 (2020)

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