Information Extraction for Additive Manufacturing Using News Data

Neha Sehgal, Andrew Crampton

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recognizing named entities like Person, Organization, Locations and Date are very useful for web mining. Named Entity Recognition (NER) is an emerging research area which aims to address problems such as Machine Translation, Question Answering Systems and Semantic Web Search. The study focuses on proposing a methodology based on the integration of an NER system and Text Analytics to provide information necessary for business in Additive Manufacturing. The study proposes a foundation of utilizing the Stanford NER system for tagging news data related to the keywords “Additive Manufacturing”. The objective is to first derive the organization names from news data. This information is useful to define the digital footprints of an organization in the Additive Manufacturing sector. The existence of an organization derived using the NER approach is validated by matching their names with companies listed on the Companies House portal. The organization names will be matched using a Fuzzy-based text matching algorithm. Further information on company profile, officers and key financial data is extracted to provide information about companies interested and working within the Additive Manufacturing sector. This data gives an insight into which companies have digital footprints in the Additive Manufacturing sector within the UK.
Original languageEnglish
Title of host publicationAdvanced Information Systems Engineering Workshops
Subtitle of host publicationCAiSE 2019 International Workshops, Rome, Italy, June 3-7, 2019, Proceedings
EditorsHenderik A. Proper, Janis Stirna
Place of PublicationCham
PublisherSpringer, Cham
Pages132-138
Number of pages7
VolumeLNBIP 349
Edition1st
ISBN (Electronic)9783030209483
ISBN (Print)9783030209476, 3030209474
DOIs
Publication statusPublished - 17 Jul 2019
Event31st International Conference on Advanced Information Systems Engineering - Rome, Italy
Duration: 3 Jun 20197 Jun 2019
Conference number: 31

Publication series

NameLecture Notes in Business Information Processing
PublisherSpringer, Cham
Volume349
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356

Conference

Conference31st International Conference on Advanced Information Systems Engineering
Abbreviated titleCAiSE 2019
CountryItaly
CityRome
Period3/06/197/06/19

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  • Cite this

    Sehgal, N., & Crampton, A. (2019). Information Extraction for Additive Manufacturing Using News Data. In H. A. Proper, & J. Stirna (Eds.), Advanced Information Systems Engineering Workshops: CAiSE 2019 International Workshops, Rome, Italy, June 3-7, 2019, Proceedings (1st ed., Vol. LNBIP 349, pp. 132-138). (Lecture Notes in Business Information Processing; Vol. 349). Springer, Cham. https://doi.org/10.1007/978-3-030-20948-3_12