Results 261 to 270 of about 2,599,171 (311)
An Expertise Transfer Framework For Autonomous Surgical Assistance
Advanced Science, EarlyView.This study introduces an expertise transfer framework for procedure‐spanning autonomous surgical assistance. By emulating expert logic through hierarchical perception, attention modeling, and knowledge graph‐based decision‐making, the system provides near‐expert surgical view assistance.
Yuan Gao +12 more
wiley +1 more source
Advanced Science, EarlyView.A large‐scale multicenter serum metabolomics study (13 centers, n = 2,149) identified a 9‐metabolite + AFP diagnostic signature for liver cancer (AUC = 0.93). Among the signature, nicotinamide (NAM) was validated as an oncometabolite: NAM enhances NAD+ synthesis, activating SIRT1 to deacetylate and stabilize HIF1α, thereby driving glycolysis, MAPK ...
Yongjie Xu +13 more
wiley +1 more source
Advanced Science, EarlyView.CsPbI3 nanostructures integrated with g‐C3N4 formed S‐scheme heterojunctions enabling efficient photocatalytic CO2 reduction and NO abatement. The g‐C3N4/CsPbI3 nanowires achieved a CO production rate of 4.6 µmol g−1 h−1, while nanocrystal composites delivered 69.5% NO removal with only 5.0% NO2 selectivity, driven by highly energetic charge carriers ...
Xiao Zhang, San Ping Jiang
wiley +1 more source
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Proceedings of the Eleventh International Conference on Data Engineering, 2002
We are given a large database of customer transactions, where each transaction consists of customer-id, transaction time, and the items bought in the transaction. We introduce the problem of mining sequential patterns over such databases. We present three algorithms to solve this problem, and empirically evaluate their performance using synthetic data.
Rakesh Agrawal 0001 +1 more
openaire +2 more sources
We are given a large database of customer transactions, where each transaction consists of customer-id, transaction time, and the items bought in the transaction. We introduce the problem of mining sequential patterns over such databases. We present three algorithms to solve this problem, and empirically evaluate their performance using synthetic data.
Rakesh Agrawal 0001 +1 more
openaire +2 more sources
Semantic pattern mining for text mining
2016 IEEE International Conference on Big Data (Big Data), 2016Pattern mining is a fundamental topic in data mining area. Many pattern mining techniques, such as closed and maximal pattern mining have been proposed for different applications. However, when calculating the frequency of a pattern, the existing techniques treat each word equally.
Xiaoli Song +2 more
openaire +1 more source
Mining interestingness measures for string pattern mining
Knowledge-Based Systems, 2010A novel method of detecting interesting patterns in strings is presented. A common way to refine the results of pattern mining algorithms is by using interestingness measures. However, the set of appropriate measures differs for each domain and problem.
Manuel Baena-García +1 more
openaire +3 more sources
From sequential pattern mining to structured pattern mining: A pattern-growth approach
Journal of Computer Science and Technology, 2004Sequential pattern mining is an important data mining problem with broad applications. However, it, is also a challenging problem since the mining may have to generate or examine a combinatorially explosive number of intermediate subsequences. Recent studies have developed two major classes of sequential pattern mining methods: (1) a candidate ...
Jiawei Han 0001 +2 more
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Mining frequent patterns with the pattern tree
New Generation Computing, 2005Mining frequent patterns with a frequent pattern tree (FP-tree in short) avoids costly candidate generation and repeatedly occurrence frequency checking against the support threshold. It therefore achieves much better performance and efficiency than Apriori-like algorithms. However, the database still needs to be scanned twice to get the FP-tree.
Hao Huang +2 more
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2016
This paper presents a new method to promote the performance of existing saliency detection algorithms. Prior bottom-up methods predict saliency maps by combining heuristic saliency cues, which may be unreliable. To remove error outputs and preserve accurate predictions, we develop a pattern mining based saliency seeds selection method.
Yuqiu Kong +4 more
openaire +2 more sources
This paper presents a new method to promote the performance of existing saliency detection algorithms. Prior bottom-up methods predict saliency maps by combining heuristic saliency cues, which may be unreliable. To remove error outputs and preserve accurate predictions, we develop a pattern mining based saliency seeds selection method.
Yuqiu Kong +4 more
openaire +2 more sources
Mining Compressing Sequential Patterns
Proceedings of the 2012 SIAM International Conference on Data Mining, 2012AbstractPattern mining based on data compression has been successfully applied in many data mining tasks. For itemset data, the Krimp algorithm based on the minimum description length (MDL) principle was shown to be very effective in solving the redundancy issue in descriptive pattern mining.
Lam, Hoang Thanh +3 more
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