Results 211 to 220 of about 938,194 (261)

Utility-Driven Mining of High Utility Episodes

2019 IEEE International Conference on Big Data (Big Data), 2019
Sequence data, e.g., complex event sequence, is more commonly seen than other types of data (e.g., transaction data) in real-world applications. For the mining task from sequence data, several problems have been formulated, such as sequential pattern mining, episode mining, and sequential rule mining.
Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Philip S. Yu   +3 more
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High-utility pattern mining: A method for discovery of high-utility item sets

Pattern Recognition, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jianying Hu, Aleksandra Mojsilovic
openaire   +2 more sources

Mining of top-k high utility itemsets with negative utility

Journal of Intelligent & Fuzzy Systems, 2021
High utility itemset mining (HUIM) with negative utility is an emerging data mining task. However, the setting of the minimum utility threshold is always a challenge when mining high utility itemsets (HUIs) with negative items. Although the top-k HUIM method is very common, this method can only mine itemsets with positive items, and the problem of ...
Sun, Rui, Han, Meng, Zhang, Chunyan, Shen, Mingyao, Du, Shiyu   +4 more
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Mining high utility itemsets

Third IEEE International Conference on Data Mining, 2004
Traditional association rule mining algorithms only generate a large number of highly frequent rules, but these rules do not provide useful answers for what the high utility rules are. We develop a novel idea of top-K objective-directed data mining, which focuses on mining the top-K high utility closed patterns that directly support a given business ...
Raymond Chan, Qiang Yang 0001, Yi-Dong Shen   +2 more
openaire   +1 more source

High-utility and diverse itemset mining

Applied Intelligence, 2021
High-utility Itemset Mining (HUIM) finds patterns from a transaction database with their utility no less than a user-defined threshold. The utility of an itemset is defined as the sum of the utilities of its items. The utility notion enables a data analyst to associate a profit score with each item and thereof to a pattern. We extend the notion of high-
Amit Verma, Siddharth Dawar, Raman Kumar, Shamkant B. Navathe, Vikram Goyal   +4 more
openaire   +1 more source

FULL-RCMA: A High Utilization EPON

IEEE Journal on Selected Areas in Communications, 2004
This paper proposes an alternate solution for Ethernet passive optical networks. Our solution uses a novel protocol named full utilization local loop request contention multiple-access protocol to efficiently provide communications in passive optical networks.
Chuan Heng Foh, Lachlan L. H. Andrew, Elaine Wong 0001, Moshe Zukerman   +3 more
openaire   +3 more sources

High utility itemsets mining with negative utility value: A survey

Journal of Intelligent & Fuzzy Systems, 2018
Mining high utility itemsets (HUIs) is a basic task of frequent itemsets mining (FIM). In recent years, a trend in FIM has been to design algorithm for mining HUIs because FIM assumes that each item can not appear more than once in a transaction and all items have the same importance (weight, unit profit, price, etc.).
Kuldeep Singh 0003, Shashank Sheshar Singh, Ajay Kumar 0006, Bhaskar Biswas   +3 more
openaire   +1 more source

Efficient Method for Mining High-Utility Itemsets Using High-Average Utility Measure

2020
Mining high-utility itemsets (HUIs) based on high-average utility measure is an important task in the data mining field. However, many of the existing algorithms are performing the mining process sequentially and do not utilize the widely available multi-core processors, thus requiring long execution times. To address this issue, we propose an extended
Nguyen Thi Thuy Loan, Trinh D. D. Nguyen, Anh Nguyen 0006, Phuoc-Nghia Tran, Cuong Trinh, Bao Huynh, Bay Vo   +6 more
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Mining High-Utility Itemsets with Multiple Minimum Utility Thresholds

Proceedings of the Eighth International C* Conference on Computer Science & Software Engineering - C3S2E '15, 2008
High-utility itemset mining (HUIM) is an emerging topic in data mining. It consists of discovering high-utility itemsets (HUIs), i.e. groups of items (itemsets) that generate a high profit in transactional databases. Several algorithms have been proposed for this task.
Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong   +3 more
openaire   +1 more source

Utilizing the power of high-performance computing

IEEE Signal Processing Magazine, 1998
The main focus of this article is the design of embedded signal processing (ESP) application software. We identify the characteristics of such applications in terms of their computational requirements, data layouts, and latency and throughput constraints. We describe an ESP application, an adaptive sonar beamformer. Then, we briefly survey the state-of-
Wenheng Liu, Viktor K. Prasanna
openaire   +1 more source