Results 281 to 290 of about 566,122 (335)

Cost-Sensitive Neighborhood Granularity Selection for Hierarchical Classification

IEEE Transactions on Knowledge and Data Engineering
Multi-label classification represented by hierarchical classification (HC) plays an important role in current large-scale problems, which can acquire a more accurate expression of data that conforms to the human multi-granularity cognitive process.
Shuai Li, Jie Yang, Huanan Bao, Deyou Xia, Qinghua Zhang, Guoyin Wang   +5 more
semanticscholar   +1 more source

Analyzing Data Granularity Levels for Insider Threat Detection Using Machine Learning

IEEE Transactions on Network and Service Management, 2020
Malicious insider attacks represent one of the most damaging threats to networked systems of companies and government agencies. There is a unique set of challenges that come with insider threat detection in terms of hugely unbalanced data, limited ground
Duc C. Le, N. Zincir-Heywood, M. Heywood
semanticscholar   +1 more source

Granular Models and Granular Outliers

IEEE Transactions on Fuzzy Systems, 2018
In this study, we propose a new design methodology of granular fuzzy models, introduce its further generalization in the form of granular fuzzy models of higher type, and discuss detection and characterization of outliers expressed with regard to the constructed information granules.
Xiubin Zhu, Witold Pedrycz, Zhiwu Li
openaire   +1 more source

Granular clustering: a granular signature of data

IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2002
The study is devoted to a granular analysis of data. We develop a new clustering algorithm that organizes findings about data in the form of a collection of information granules-hyperboxes. The clustering carried out here is an example of a granulation mechanism.
W, Pedrycz, A, Bargiela
openaire   +2 more sources

Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection

The Web Conference
In light of the remarkable advancements made in time-series anomaly detection(TSAD), recent emphasis has been placed on exploiting the frequency domain as well as the time domain to address the difficulties in precisely detecting pattern-wise anomalies ...
Youngeun Nam, Susik Yoon, Yooju Shin, Minyoung Bae, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee   +6 more
semanticscholar   +1 more source

Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion

International Conference on Information and Knowledge Management, 2021
Stock trend prediction plays a crucial role in quantitative investing. Given the prediction task on a certain granularity (e.g., daily trend), a large portion of existing studies merely leverage market data of the same granularity (e.g., daily market ...
Min Hou, Chang Xu, Yang Liu, Weiqing Liu, Jiang Bian, Le Wu, Zhi Li, Enhong Chen, Tie-Yan Liu   +8 more
semanticscholar   +1 more source

Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation

International Conference on Computational Linguistics
Integrating information from various reference databases is a major challenge for Retrieval-Augmented Generation (RAG) systems because each knowledge source adopts a unique data structure and follows different conventions.
Zijie Zhong, Hanwen Liu, Xiao Cui, Xiaofan Zhang, Zengchang Qin   +4 more
semanticscholar   +1 more source

Granular algebra for modeling granular systems and granular computing

2009 8th IEEE International Conference on Cognitive Informatics, 2009
Granular computing provides a new perspective on computing architectures and behaviors. This paper presents a recent development in denotational mathematics known as granular algebra, which enables a rigorous treatment of computing granules as a generic abstract mathematical structure and granular behaviors as a set of algebraic operations. An abstract
openaire   +1 more source

Sequential three-way decisions via multi-granularity

Information Sciences, 2020
Three-way decisions provide a trisecting-and-acting framework for complex problem solving. For a cost-sensitive decision-making problem under multiple levels of granularity, sequential three-way decisions have come into being.
J. Qian, Caihui Liu, Duoqian Miao, Xiaodong Yue   +3 more
semanticscholar   +1 more source

A matrix factorization based dynamic granularity recommendation with three-way decisions

Knowledge-Based Systems, 2020
Recommender systems (RSs) are effective technologies and tools used to deal with the problems of information overload, and have been developed rapidly in nearly two decades.
Dun Liu, Xiaoqing Ye
semanticscholar   +1 more source