Название: Intelligent Processing Practices and Tools for E-Commerce Data, Information, and KnowledgeАвтор: Honghao Gao, Jung Yoon Kim, Walayat Hussain
Издательство: Springer
Год: 2022
Страниц: 124
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
This book discusses recent research and applications about intelligent processing practices and tools for e-commerce data, information and knowledge. The authors first explain how advances in intelligent processing of data, information and knowledge that has wildly been used in e-commerce applications. They then show how this brings new opportunities and challenges for processing e-commerce data, information and knowledge. The book, made up of contributions from both academia and industry, aims to present advances in Artificial Intelligence (AI) to collect, process, and mining Data, information and knowledge, such as new algorithms and techniques in the field, foundational theory and systems, as well as practical e-commerce applications. Some of the topics discussed include AI for e-commerce, such as Machine Learning (ML), Deep Learning (DL); personalized service recommendation to e-commerce; modeling, description, and verification for data, information and knowledge; and task scheduling and performance optimization for large-scale concurrency.
With the rapid development of 5G and mobile devices, there are many new e-commerce systems used in our daily life, such as wireless payment and recommender systems. Along with this, a large number of Data, Information, and Knowledge have emerged, with features of complexity, diversity, and crossover. How to use Intelligent Processing to handle E-Commerce Data, Information, and Knowledge is a new opportunity and challenge. AI for e-commerce, such as Machine Learning and Deep Learning, can be used in information modeling, data mining, knowledge description, and system verification.
Supervised methods, especially deep learning, are attractive for achieving a better performance and are the focus in our work. However, a lack of labeled data is one of the big challenges for training deep neural networks. In this work, we employ the idea of long-distance supervision to automatically create large amounts of gold standard data. In the e-commerce field, since queries are related to products, we build a dictionary by crawling brand names, product names, attribute names, and attribute values from the product detail pages of online shopping platforms. Then, a simple max-matching algorithm can be used to segment queries by matching subsequences in queries with the words in the dictionary.
The book, including six chapters made up of contributions from the academic and industry, aims to present advances in Artificial Intelligence to collect, process, and mining Data, Information, and Knowledge.
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