Results 271 to 280 of about 10,424,890 (336)

On a Method of Sequential Pattern Recognition

IEEE Transactions on Computers, 1972
In this paper, a multistage linear programming method of pattern recognition is proposed. The usual n-dimensional linear program has been split up into n stages of a one-dimensional linear program in such a way that more and more patterns belonging to two classes A and B are correctly classified as we proceed to higher and higher stages.
A. Som, A. K. Nath
openaire   +2 more sources

Mining Compressing Sequential Patterns

Proceedings of the 2012 SIAM International Conference on Data Mining, 2012
AbstractPattern 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, Moerchen, Fabian, Fradkin, Dmitriy, Calders, Toon   +3 more
openaire   +5 more sources

Mining Top- ${k}$ Useful Negative Sequential Patterns via Learning

IEEE Transactions on Neural Networks and Learning Systems, 2019
As an important tool for behavior informatics, negative sequential patterns (NSPs) (such as missing a medical treatment) are sometimes much more informative than positive sequential patterns (PSPs) (e.g., attending a medical treatment) in many ...
Xiangjun Dong, Ping Qiu, Jin-Hu Lu, Long-Bing Cao, Tiantian Xu   +4 more
semanticscholar   +1 more source

Mining conditional discriminative sequential patterns

Information Sciences, 2019
Discriminative sequential pattern mining is one of the most important topics in pattern mining, which has a very wide range of applications. Discriminative sequential pattern mining is intended to extract sequential patterns with significant differences ...
Zeng-You He, Simeng Zhang, Feiyang Gu, Jun Wu   +3 more
semanticscholar   +1 more source

On Suboptimal Sequential Pattern Recognition

IEEE Transactions on Computers, 1968
Abstract—In this note, three suboptimal solutions are obtained for the joint sequential feature selection and pattern classification problem. These solutions allow the comparison of two distinctly different approximations to the optimal procedure. One approximation involves simplifying assumptions on the underlying distribution of features for each ...
Gerald P. Cardillo, King-Sun Fu
openaire   +1 more source

Mining Sequential Patterns in Uncertain Databases Using Hierarchical Index Structure

arXiv.org
In this uncertain world, data uncertainty is inherent in many applications and its importance is growing drastically due to the rapid development of modern technologies.
Kashob Kumar Roy, Md Hasibul Haque Moon, Md Mahmudur Rahman, Chowdhury Farhan Ahmed, C. Leung   +4 more
semanticscholar   +1 more source

Sequential Pattern Mining with Wildcards

2010 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010
Sequential pattern mining is an important research task in many domains, such as biological science. In this paper, we study the problem of mining frequent patterns from sequences with wildcards. The user can specify the gap constraints with flexibility. Given a subject sequence, a minimal support threshold and a gap constraint, we aim to find frequent
Fei Xie 0002, Xindong Wu 0001, Xuegang Hu, Jun Gao 0006, Dan Guo 0001, Yulian Fei, Ertian Hua   +6 more
openaire   +1 more source

Mining Sequential Patterns with Pattern Constraint

2015
Mining sequential patterns is to find the sequential purchasing behaviors for most of the customers. There were many algorithms proposed for discovering all the sequential patterns. However, users may be only interested in certain items or behaviors.
Show-Jane Yen, Yue-Shi Lee, Bai-En Shie, Yeuan-Kuen Lee   +3 more
openaire   +1 more source

Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding

Web Search and Data Mining, 2018
Top-N sequential recommendation models each user as a sequence of items interacted in the past and aims to predict top-N ranked items that a user will likely interact in a »near future».
Jiaxi Tang, Ke Wang
semanticscholar   +1 more source

On progressive sequential pattern mining

Proceedings of the 15th ACM international conference on Information and knowledge management - CIKM '06, 2006
When sequential patterns are generated, the newly arriving patterns may not be identified as frequent sequential patterns due to the existence of old data and sequences. In practice, users are usually more interested in the recent data than the old ones.
Jen-Wei Huang, Chi-Yao Tseng, Jian Chih Ou, Ming-Syan Chen   +3 more
openaire   +2 more sources