Publication detail

Novel Big Data Approach for Text Supported Service Operations Management

POVODA, L. BURGET, R. RAJNOHA, M. BREZANY, P.

Original Title

Novel Big Data Approach for Text Supported Service Operations Management

Type

book chapter

Language

English

Original Abstract

Operations management is being applied across all industry sectors and offers more accurate decision making, cost saving and a path to lean production. All depend on proper information, which is a valuable input for operations management and can represent the key to gain competitive advantage. Thanks to the information, we can improve and optimize processes and react to problems before they even appear. Unfortunately, getting this knowledge is often a challenging task. It is estimated that only a small portion of publicly available data can be considered as valuable. Considering the size of today's data storage, it is out of possibilities for anyone to read them all and operatively react to the changing environment and competition. In case of the text data, they are often written in many different languages, use different expert domains or customer segments, who have their own specific language style. To gain valuable information from this data, it is necessary to know each particular language (not necessarily human, but also machine generated) and grammar. This chapter presents the latest advances in artificial intelligence for the text data analysis and operations management. First, we provide the state of the art of the text processing approaches, then we discuss selected use-cases from the field of operations management and how the latest methods can help to solve those problems. The last part of the chapter outlines some ideas for further improvement of the current approaches and how to effectively analyse data in a multilingual environment and decrease memory demands.

Keywords

Big data; Decision making; Digital storage; Text processing; Changing environment; Competitive advantage; Cost saving; Data storage; Decisions makings; Industry sectors; Management IS; Operation management; Service operations management; Text data;, Competition

Authors

POVODA, L.; BURGET, R.; RAJNOHA, M.; BREZANY, P.

Released

1. 12. 2022

Publisher

Springer Science and Business Media Deutschland GmbH

ISBN

978-3-030-87304-2

Book

Big Data and Blockchain for Service Operations Management: Studies in Big Data

Edition

98

Pages from

163

Pages to

189

Pages count

27

URL

https://books.google.cz/books?id=I7NeEAAAQBAJ&pg=PA163&lpg=PA163&dq=10.1007/978-3-030-87304-2_6&source=bl&ots=Vhot6SHok2&sig=ACfU3U0rOHVxYsT1yVAIafaxLAv1J6_WVw&hl=cs&sa=X&ved=2ahUKEwiDudej5879AhWGQ_EDHQFiC7gQ6AF6BAgIEAM#v=onepage&q=10.1007%2F978-3-030-87304-2_6&f=false

BibTex

@inbook{BUT183094,
  author="Lukáš {Povoda} and Radim {Burget} and Martin {Rajnoha} and Peter {Brezany}",
  title="Novel Big Data Approach for Text Supported Service Operations Management",
  booktitle="Big Data and Blockchain for Service Operations Management: Studies in Big Data",
  year="2022",
  publisher="Springer Science and Business Media Deutschland GmbH",
  series="98",
  pages="163--189",
  doi="10.1007/978-3-030-87304-2\{_}6",
  isbn="978-3-030-87304-2",
  url="https://books.google.cz/books?id=I7NeEAAAQBAJ&pg=PA163&lpg=PA163&dq=10.1007/978-3-030-87304-2_6&source=bl&ots=Vhot6SHok2&sig=ACfU3U0rOHVxYsT1yVAIafaxLAv1J6_WVw&hl=cs&sa=X&ved=2ahUKEwiDudej5879AhWGQ_EDHQFiC7gQ6AF6BAgIEAM#v=onepage&q=10.1007%2F978-3-030-87304-2_6&f=false"
}