Results 81 to 90 of about 4,248,745 (299)
KIPS Transactions on Software and Data Engineering, 2016 현존하는 빈발 패턴 마이닝 방법은 대부분 시간 효율성을 목표로 하고, 물리적 메모리 사용에 매우 의존적이다. 하지만 빅데이터 시대가 도래함에 따라 실제 세상의 데이터베이스는 급속도로 증가하고 있으며, 그에 따라 기존의 방법으로 현실적인 거대한 양의 데이터를 마이닝하기에 물리적 메모리 공간이 부족한 실정이다. 이러한 문제를 해결하기 위해, 빈발 패턴 마이닝의 메모리 의존성을 줄이기 위한 보조저장장치 기반의 연구들이 진행되었으나, 메모리 기반의 방법들에 비해 처리 시간이 너무 많이 소비된다는 한계가 있었다.
Jung-Hun Lee, Youn-A Min
openaire +2 more sources
Discovering Closed Frequent Patterns in Moving Trajectory Database
, 2012 The increasing availability of tracking devices bring larger amounts of trajectories representing people's moving location histories. In this paper, we aimed to mine closed frequent patterns in moving trajectory database.
Wang L(王亮) +3 more
core
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Young adult childhood cancer survivors (YA‐CCS) have an increased risk of treatment‐related health complications throughout their lives. Lifelong survivorship care is recommended, yet many YA‐CCS experience disruptions in care during pediatric‐to‐adult transitions and do not receive recommended survivorship care.
Kevin Shanchen Pu +8 more
wiley +1 more source
Mining Frequent Patterns in Evolving Graphs
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018 Given a labeled graph, the frequent-subgraph mining (FSM) problem asks to find all the $k$-vertex subgraphs that appear with frequency greater than a given threshold. FSM has numerous applications ranging from biology to network science, as it provides a compact summary of the characteristics of the graph. However, the task is challenging, even more so
Nasir, Muhammad Anis Uddin +4 more
openaire +7 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Febrile neutropenia (FN) is a frequent and serious complication in children receiving cancer therapy. Standardizing FN management across Asia is challenging due to variable healthcare infrastructure, diagnostic capacity, and infection patterns; however, it could improve resource use and patient outcomes.
Joliza Patricia Cañeba +29 more
wiley +1 more source
On computing, storing and querying frequent patterns
, 2003 Extensive efforts have been devoted to developing efficient algorithms for mining frequent patterns. However, frequent pattern mining remains a time-consuming process, especially for very large datasets.
Lou, W. +7 more
core +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Therapeutic apheresis (TA) is an established treatment modality for hematologic, neurologic, and immunologic disorders, yet access remains severely limited in sub‐Saharan Africa. Donor apheresis, including platelet apheresis collection from healthy donors, represents an important complementary modality supporting blood product ...
Nosa Bazuaye +33 more
wiley +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida +6 more
wiley +1 more source
Algorithms for Extracting Frequent Episodes in the Process of Temporal Data Mining [PDF]
An important aspect in the data mining process is the discovery of patterns having a great influence on the studied problem. The purpose of this paper is to study the frequent episodes data mining through the use of parallel pattern discovery algorithms.
Alexandru PIRJAN
core
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Establishing a comprehensive apheresis medicine program in a resource‐constrained setting presents significant structural, financial, and logistical challenges. Despite the growing clinical importance of apheresis services globally, published experience from sub‐Saharan Africa remains sparse.
Folasade Adelekan‐Popoola +4 more
wiley +1 more source