Non-redundant sequential association rule mining based on closed sequential patterns [PDF]
, 2010 In many applications, e.g., bioinformatics, web access traces, system utilisation logs, etc., the data is naturally in the form of sequences. People have taken great interest in analysing the sequential data and finding the inherent characteristics or ...
Zang, Hao
core
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
NetNMSP: Nonoverlapping maximal sequential pattern mining. [PDF]
Appl Intell (Dordr), 2022 Li Y, Zhang S, Guo L, Liu J, Wu Y, Wu X.
europepmc +1 more source
Detecting news topics from microblogs using sequential pattern mining [PDF]
, 2014 This thesis presents a sequential pattern based model (PMM) to detect news topics from a popular microblogging platform, Twitter. PMM captures key topics and measures their importance using pattern properties and Twitter characteristics. This study shows
Lau, Cher Han
core
Data‐Driven Materials Science for Energy‐Sustainable Applications
Advanced Materials, EarlyView.Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
Applying Sequential Pattern Mining to Investigate the Temporal Relationships between Commonly Occurring Internal Medicine Diseases and Intervals for the Risk of Concurrent Disease in Canine Patients. [PDF]
Animals (Basel), 2023 Lee SJ, Kim JH.
europepmc +1 more source
Parallel research of sequential pattern data mining algorithm
, 2008 Sequential pattern has important applications in many areas and a large number of data and patterns need efficient and scalable parallel algorithm. In light of the widespread problem in current sequential pattern data mining algorithm and on the basis of
Xi1 +7 more
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Advanced Materials, EarlyView.An engineered Trojan Mycobacterium, developed via a “peeling‐off and masking‐up” strategy, functions as a powerful splenic myelopoiesis converter. This spleen‐targeted nanomedicine induces trained immunity to reprogram immunosuppressive myeloid reservoirs into antitumoral effectors.
Jin‐Ho Choi +5 more
wiley +1 more source
Parallel sequential pattern mining on distributed system
, 2010 碩士本研究以提昇循序樣本探勘效率為目標，發展了一套結合多部電腦的分散式探勘系統。首先，由於直接以支持度預測子任務工作量並不準確，我們提出新的工作量預測方法。而後，本研究提出了一套負載平衡演算法-ADLB，結合動態與靜態分配的特點，對於任務採取分段分配，以達成負載平衡並降低通訊負擔。此外，我們也引用並改進文獻[20]中有關演算法切換的概念，以取得更大幅度效能改善。為驗證系統效能，我們結合了16部電腦進行分散式探勘，實驗結果顯示，本系統在各種不同節點數目下均具有良好加速比，顯示其具有處理大型資料之潛力 ...
郭家君; Guo, Jia-jyun
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A hypoglycemia early alarm method for patients with type 1 diabetes based on multi-dimensional sequential pattern mining. [PDF]
Heliyon, 2022 Ma N, Yu X, Yang T, Zhao Y, Li H.
europepmc +1 more source