Time-Aware Conversion Prediction for E-Commerce

Nonfiction, Computers, Advanced Computing, Theory, Artificial Intelligence, Business & Finance
Cover of the book Time-Aware Conversion Prediction for E-Commerce by Wendi Ji, Xiaoling Wang, Aoying Zhou;;, World Scientific Publishing Company
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Author: Wendi Ji, Xiaoling Wang, Aoying Zhou;; ISBN: 9789813224735
Publisher: World Scientific Publishing Company Publication: January 17, 2018
Imprint: WSPC Language: English
Author: Wendi Ji, Xiaoling Wang, Aoying Zhou;;
ISBN: 9789813224735
Publisher: World Scientific Publishing Company
Publication: January 17, 2018
Imprint: WSPC
Language: English

This unique compendium provides a novel research on how time influences the conversions of advertising and product recommendation in E-commerce. It proposes time-aware conversion prediction models to solve the problem — what products should be recommended for a given period to maximize conversion? The volume also presents a series of researches on how to build data-driven attribution models to allocate the time-sensitive contribution of advertisements to the conversion. This must-have reference text will be invaluable for researchers, professionals, academics and graduate students keen in databases and artificial intelligence.

Contents:

  • Introduction
  • Basic Conversion Prediction Models
  • Modeling of the Conversion Delay
  • Time-Aware Conversion Prediction
  • Multi-Touch Attribution Analysis in Online Advertising
  • Accumulative MTA Analysis in Online Advertising
  • Conclusions

Readership: Researchers, academics, professionals and graduate students in databases, artificial intelligence and pattern recognition.
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View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This unique compendium provides a novel research on how time influences the conversions of advertising and product recommendation in E-commerce. It proposes time-aware conversion prediction models to solve the problem — what products should be recommended for a given period to maximize conversion? The volume also presents a series of researches on how to build data-driven attribution models to allocate the time-sensitive contribution of advertisements to the conversion. This must-have reference text will be invaluable for researchers, professionals, academics and graduate students keen in databases and artificial intelligence.

Contents:

Readership: Researchers, academics, professionals and graduate students in databases, artificial intelligence and pattern recognition.
0

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