Keywords:
Pricing-Data processing.
;
Electronic books.
Type of Medium:
Online Resource
Pages:
1 online resource (62 pages)
Edition:
1st ed.
ISBN:
9789811647024
Series Statement:
SpringerBriefs in Applied Sciences and Technology Series
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=6714605
Language:
English
Note:
Intro -- Preface I -- Preface II -- Acknowledgements -- Contents -- Acronyms -- 1 Pricing Based on Product Descriptions: Problem, Data and Methods -- 1.1 Pricing Problems -- 1.1.1 Pricing Products -- 1.2 Data Description -- 1.2.1 Car Description from Customs Declarations -- 1.2.2 Car Description from Websites -- References -- 2 Machine Learning and Ensemble Methods -- 2.1 Introduction to Machine Learning -- 2.2 Linear Classification -- 2.3 Support Vector Machine -- 2.4 Decision Tree -- 2.5 Ensemble Methods -- References -- 3 Quantifying the Qualitative Features -- 3.1 Qualitative Features -- 3.2 Integer Encoding -- 3.3 One-Hot Encoding -- 3.4 Entity Embedding with Neural Networks -- 3.4.1 Neural Networks -- 3.4.2 Entity Embedding -- 3.5 Applications -- References -- 4 Deep Learning Model for Product Classification -- 4.1 Hierarchical Text Classification Problem and Applications -- 4.1.1 HTC Problem in Product Classification Based on Its Description -- 4.1.2 BERT Model for Text Classification -- 4.1.3 BERT Model with Multi-layer Loss Function -- 4.2 Training Data -- 4.3 Evaluation Metrics -- 4.4 Experiment -- References -- 5 Product Feature Extraction from the Descriptions -- 5.1 Semi-automatic Labeling Model Based on Doccano Framework -- 5.1.1 Labeling Car Description Data Problem and Overall Labeling Model -- 5.1.2 Expert-Based Labeling Process -- 5.1.3 Machine Learning-Based Labeling Process -- 5.2 Extracting Features of Vehicles from the Descriptions -- 5.2.1 Data Description -- 5.2.2 Building Model -- 5.2.3 Evaluating Model -- References -- Appendix Glossary.
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