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Trends and Applications in Knowledge Discovery and Data Mining

Overview of attention for book
Trends and Applications in Knowledge Discovery and Data Mining
Springer Nature Singapore

Table of Contents

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    Book Overview
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    Chapter 1 Evaluation of Orca 2 Against Other LLMs for Retrieval Augmented Generation
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    Chapter 2 Toward Interpretable Graph Classification via Concept-Focused Structural Correspondence
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    Chapter 3 InteraRec : Interactive Recommendations Using Multimodal Large Language Models
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    Chapter 4 Research on Dynamic Community Detection Method Based on Multi-dimensional Feature Information of Community Network
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    Chapter 5 From Tweets to Token Sales: Assessing ICO Success Through Social Media Sentiments
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    Chapter 6 Enhanced Graph Neural Network for Session-Based Recommendation with Static and Dynamic Information
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    Chapter 7 Construction of Academic Innovation Chain Based on Multi-level Clustering of Field Literature
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    Chapter 8 DLVS4Audio2Sheet: Deep Learning-Based Vocal Separation for Audio into Music Sheet Conversion
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    Chapter 9 Explainable AI for Stress and Depression Detection in the Cyberspace and Beyond
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    Chapter 10 Finding Foundation Models for Time Series Classification with a PreText Task
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    Chapter 11 Next Item and Interval Prediction of New Users Using Meta-Learning on Dynamic Network
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    Chapter 12 Adaptive Knowledge Sharing in Multi-Task Learning: Insights from Electricity Data Analysis
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    Chapter 13 Handling Concept Drift in Non-stationary Bandit Through Predicting Future Rewards
Attention for Chapter 10: Finding Foundation Models for Time Series Classification with a PreText Task
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Article details
Chapter title
Finding Foundation Models for Time Series Classification with a PreText Task
Chapter number 10
Book title
Trends and Applications in Knowledge Discovery and Data Mining
DOI 10.1007/978-981-97-2650-9_10
Book ISBNs
978-9-81-972649-3, 978-9-81-972650-9
Authors

Ismail-Fawaz, Ali, Devanne, Maxime, Berretti, Stefano, Weber, Jonathan, Forestier, Germain

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Student > Doctoral Student 1 13%
Unknown 5 63%
Readers by discipline
Readers by discipline Count As %
Computer Science 2 25%
Unknown 6 75%