Unsupervised Text Annotations

Tanya Braun; Felix Kuhr; Ralf Möller

Unsupervised Text Annotations

Tanya Braun, Felix Kuhr, Ralf Möller

Institut für Informationssysteme

Abstract

We introduce the unsupervised text annotation model UTA, which iteratively populates a document-specific database containing the related symbolic content description. The model identifies the most related documents using the text of documents and the symbolic content description. UTA extends the database of one document with data from related documents without ignoring the precision.

Originalsprache	Englisch
Titel	Proceedings of the 6th Workshop on Dynamics of Knowledge and Belief (DKB-2017) and the 5th Workshop KI Kognition (KIK-2017) co-located with 40th German Conference on Artificial Intelligence (KI 2017)
Seitenumfang	8
Band	1928
Herausgeber (Verlag)	CEUR-WS.org
Erscheinungsdatum	01.09.2017
Seiten	23-30
Publikationsstatus	Veröffentlicht - 01.09.2017
Veranstaltung	6th Workshop on Dynamics of Knowledge and Belief and the 5th Workshop KI and Kognition - Dortmund, Deutschland Dauer: 26.09.2017 → 26.09.2017 Konferenznummer: 130603

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 3 – Gesundheit und Wohlergehen
SDG 9 – Industrie, Innovation und Infrastruktur

DFG-Fachsystematik

409-06 Informationssysteme, Prozess- und Wissensmanagement

Dokumente

http://ceur-ws.org/Vol-1928/paper2.pdf

Weitere Links

https://www.scopus.com/pages/publications/85030127200

Zitieren

Braun, T., Kuhr, F., & Möller, R. (2017). Unsupervised Text Annotations. in Proceedings of the 6th Workshop on Dynamics of Knowledge and Belief (DKB-2017) and the 5th Workshop KI Kognition (KIK-2017) co-located with 40th German Conference on Artificial Intelligence (KI 2017) (Band 1928, S. 23-30). (CEUR Workshop Proceedings; Band 1928). CEUR-WS.org. http://ceur-ws.org/Vol-1928/paper2.pdf

@inproceedings{14df77063f6d43108cfe39ded7f59abf,

title = "Unsupervised Text Annotations",

abstract = "We introduce the unsupervised text annotation model UTA, which iteratively populates a document-specific database containing the related symbolic content description. The model identifies the most related documents using the text of documents and the symbolic content description. UTA extends the database of one document with data from related documents without ignoring the precision. ",

author = "Tanya Braun and Felix Kuhr and Ralf M{\"o}ller",

year = "2017",

month = sep,

day = "1",

language = "English",

volume = "1928",

series = "CEUR Workshop Proceedings",

publisher = "CEUR-WS.org",

pages = "23--30",

booktitle = "Proceedings of the 6th Workshop on Dynamics of Knowledge and Belief (DKB-2017) and the 5th Workshop KI Kognition (KIK-2017) co-located with 40th German Conference on Artificial Intelligence (KI 2017)",

note = "6th Workshop on Dynamics of Knowledge and Belief and the 5th Workshop KI and Kognition, DKB-KIK 2017 ; Conference date: 26-09-2017 Through 26-09-2017",

}

Braun, T, Kuhr, F & Möller, R 2017, Unsupervised Text Annotations. in Proceedings of the 6th Workshop on Dynamics of Knowledge and Belief (DKB-2017) and the 5th Workshop KI Kognition (KIK-2017) co-located with 40th German Conference on Artificial Intelligence (KI 2017). Bd. 1928, CEUR Workshop Proceedings, Bd. 1928, CEUR-WS.org, S. 23-30, 6th Workshop on Dynamics of Knowledge and Belief and the 5th Workshop KI and Kognition, Dortmund, Nordrhein-Westfalen, Deutschland, 26.09.17. <http://ceur-ws.org/Vol-1928/paper2.pdf>

Unsupervised Text Annotations. / Braun, Tanya; Kuhr, Felix; Möller, Ralf.
Proceedings of the 6th Workshop on Dynamics of Knowledge and Belief (DKB-2017) and the 5th Workshop KI Kognition (KIK-2017) co-located with 40th German Conference on Artificial Intelligence (KI 2017). Band 1928 CEUR-WS.org, 2017. S. 23-30 (CEUR Workshop Proceedings; Band 1928).

Publikation: Kapitel in Büchern/Berichten/Konferenzbänden › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Unsupervised Text Annotations

AU - Braun, Tanya

AU - Kuhr, Felix

AU - Möller, Ralf

N1 - Conference code: 130603

PY - 2017/9/1

Y1 - 2017/9/1

N2 - We introduce the unsupervised text annotation model UTA, which iteratively populates a document-specific database containing the related symbolic content description. The model identifies the most related documents using the text of documents and the symbolic content description. UTA extends the database of one document with data from related documents without ignoring the precision.

AB - We introduce the unsupervised text annotation model UTA, which iteratively populates a document-specific database containing the related symbolic content description. The model identifies the most related documents using the text of documents and the symbolic content description. UTA extends the database of one document with data from related documents without ignoring the precision.

UR - https://www.scopus.com/pages/publications/85030127200

M3 - Conference contribution

VL - 1928

T3 - CEUR Workshop Proceedings

SP - 23

EP - 30

BT - Proceedings of the 6th Workshop on Dynamics of Knowledge and Belief (DKB-2017) and the 5th Workshop KI Kognition (KIK-2017) co-located with 40th German Conference on Artificial Intelligence (KI 2017)

PB - CEUR-WS.org

T2 - 6th Workshop on Dynamics of Knowledge and Belief and the 5th Workshop KI and Kognition

Y2 - 26 September 2017 through 26 September 2017

ER -