Results 11 to 20 of about 2,740,047 (370)
Unsupervised Classification of Opinions
Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2016 Opinion mining is gaining more interest thanks to the ever growing data available on the internet. This work proposes an unsupervised approach that clusters opinions in fine grain ranges. The approach is able to generate its own seed words for better applicability to the context and eliminating user input.
Mihaela Dinsoreanu +2 more
openaire +2 more sources
Unsupervised Classification During Time-Series Model Building. [PDF]
Multivariate Behav Res, 2017 Gates KM +4 more
europepmc +2 more sources
Unsupervised classification of SDSS galaxy spectra [PDF]
Astronomy & Astrophysics, 2021 Context. Defining templates of galaxy spectra is useful to quickly characterise new observations and organise databases from surveys. These templates are usually built from a pre-defined classification based on other criteria. Aims.
D. Fraix-Burnet +2 more
semanticscholar +1 more source
Unsupervised Domain Adaptation With Dense-Based Compaction for Hyperspectral Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Enormously hard work of label obtaining leads to the lack of enough annotated samples in the hyperspectral imagery (HSI). The mentioned reality inferred the unsupervised classification performance barely satisfactorily.
Chunyan Yu +4 more
doaj +1 more source
Research on Seismic Signal Analysis Based on Machine Learning
Applied Sciences, 2022 In this paper, the time series classification frontier method MiniRocket was used to classify earthquakes, blasts, and background noise. From supervised to unsupervised classification, a comprehensive analysis was carried out, and finally, the supervised
Xinxin Yin +6 more
doaj +1 more source
Calibrated One-Class Classification for Unsupervised Time Series Anomaly Detection [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2022 Time series anomaly detection is instrumental in maintaining system availability in various domains. Current work in this research line mainly focuses on learning data normality deeply and comprehensively by devising advanced neural network structures ...
Hongzuo Xu +5 more
semanticscholar +1 more source
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews [PDF]
Annual Meeting of the Association for Computational Linguistics, 2002 This paper presents a simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (thumbs down). The classification of a review is predicted by the average semantic orientation of the phrases in the review
Peter D. Turney
semanticscholar +1 more source
Contrastive Learning Based on Transformer for Hyperspectral Image Classification
Applied Sciences, 2021 Recently, deep learning has achieved breakthroughs in hyperspectral image (HSI) classification. Deep-learning-based classifiers require a large number of labeled samples for training to provide excellent performance.
Xiang Hu +4 more
doaj +1 more source
Momentum Contrast for Unsupervised Visual Representation Learning [PDF]
Computer Vision and Pattern Recognition, 2019 We present Momentum Contrast (MoCo) for unsupervised visual representation learning. From a perspective on contrastive learning as dictionary look-up, we build a dynamic dictionary with a queue and a moving-averaged encoder. This enables building a large
Kaiming He +4 more
semanticscholar +1 more source
Land Cover Changes Based on Landsat Imagery Interpretation
Jurnal Teknik Pertanian Lampung, 2023 This paper presents the use of satellite data (i.e., Landsat-5 & Landsat-8) to interpret the change of land cover from 1997 to 2020. The study area covers the administrative boundary of Lumajang Regency.
Chairiyah Umi Rahayu +4 more
doaj +1 more source