Coupling information extraction and data mining for ontology learning in PARMENIDES

Myra Spiliopoulou; Fabio Rinaldi; William Black; Gian Piero Zarri; Roland Mueller; Marko Brunzel; Charalampos Theodoulidis; Giorgos Orphanos; Michael Hess; James Dowdall; John McNaught; Maghi King; Andreas Persidis; Luc Bernard

Coupling information extraction and data mining for ontology learning in PARMENIDES

Myra Spiliopoulou, Fabio Rinaldi, William Black, Gian Piero Zarri, Roland Mueller, Marko Brunzel, Charalampos Theodoulidis, Giorgos Orphanos, Michael Hess, James Dowdall, John McNaught, Maghi King, Andreas Persidis, Luc Bernard

Management Sciences

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

Abstract

Strategic decision making, especially in the areas of business intelligence and competitive intelligence, requires the acquisition of decision-relevant information pieces like market trends, fusions and company values. This information is extracted by pre-processing and querying multiple sources, combining and condensing the findings. It is characteristic that the extraction process is resource intensive and has to be performed regularly and quite frequently. In the research project PARMENIDES, we are developing methods that establish ontologies over an application domain, annotate documents with the ontology components and identify the entities in them, so that we can decompose business into conventional queries towards entities and XML-annotated texts.

Original language	English
Title of host publication	Proceedings of RIAO '04
Subtitle of host publication	Coupling approaches, coupling media and coupling languages for information retrieval
Place of Publication	Paris
Publisher	Centre de hautes études internationales d'informatique documentaire
Pages	156-169
ISBN (Print)	2905450096
Publication status	Published - 2004

Keywords

information extraction
text mining
ontologies
business intelligence
competitive intelligence

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http://dl.acm.org/ft_gateway.cfm?id=2816287Licence: Other

Cite this

Spiliopoulou, M., Rinaldi, F., Black, W., Zarri, G. P., Mueller, R., Brunzel, M., Theodoulidis, C., Orphanos, G., Hess, M., Dowdall, J., McNaught, J., King, M., Persidis, A., & Bernard, L. (2004). Coupling information extraction and data mining for ontology learning in PARMENIDES. In Proceedings of RIAO '04: Coupling approaches, coupling media and coupling languages for information retrieval (pp. 156-169). Centre de hautes études internationales d'informatique documentaire. http://dl.acm.org/ft_gateway.cfm?id=2816287

@inproceedings{5e4e0e0a0494468e927fa6c8f8db7c50,

title = "Coupling information extraction and data mining for ontology learning in PARMENIDES",

abstract = "Strategic decision making, especially in the areas of business intelligence and competitive intelligence, requires the acquisition of decision-relevant information pieces like market trends, fusions and company values. This information is extracted by pre-processing and querying multiple sources, combining and condensing the findings. It is characteristic that the extraction process is resource intensive and has to be performed regularly and quite frequently. In the research project PARMENIDES, we are developing methods that establish ontologies over an application domain, annotate documents with the ontology components and identify the entities in them, so that we can decompose business into conventional queries towards entities and XML-annotated texts.",

keywords = "information extraction, text mining, ontologies, business intelligence, competitive intelligence",

author = "Myra Spiliopoulou and Fabio Rinaldi and William Black and Zarri, {Gian Piero} and Roland Mueller and Marko Brunzel and Charalampos Theodoulidis and Giorgos Orphanos and Michael Hess and James Dowdall and John McNaught and Maghi King and Andreas Persidis and Luc Bernard",

year = "2004",

language = "English",

isbn = "2905450096",

pages = "156--169",

booktitle = "Proceedings of RIAO '04",

publisher = "Centre de hautes {\'e}tudes internationales d'informatique documentaire",

address = "France",

}

Spiliopoulou, M, Rinaldi, F, Black, W, Zarri, GP, Mueller, R, Brunzel, M, Theodoulidis, C, Orphanos, G, Hess, M, Dowdall, J, McNaught, J, King, M, Persidis, A & Bernard, L 2004, Coupling information extraction and data mining for ontology learning in PARMENIDES. in Proceedings of RIAO '04: Coupling approaches, coupling media and coupling languages for information retrieval. Centre de hautes études internationales d'informatique documentaire, Paris, pp. 156-169. <http://dl.acm.org/ft_gateway.cfm?id=2816287>

Coupling information extraction and data mining for ontology learning in PARMENIDES. / Spiliopoulou, Myra; Rinaldi, Fabio; Black, William et al.
Proceedings of RIAO '04: Coupling approaches, coupling media and coupling languages for information retrieval. Paris: Centre de hautes études internationales d'informatique documentaire, 2004. p. 156-169.

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Coupling information extraction and data mining for ontology learning in PARMENIDES

AU - Spiliopoulou, Myra

AU - Rinaldi, Fabio

AU - Black, William

AU - Zarri, Gian Piero

AU - Mueller, Roland

AU - Brunzel, Marko

AU - Theodoulidis, Charalampos

AU - Orphanos, Giorgos

AU - Hess, Michael

AU - Dowdall, James

AU - McNaught, John

AU - King, Maghi

AU - Persidis, Andreas

AU - Bernard, Luc

PY - 2004

Y1 - 2004

N2 - Strategic decision making, especially in the areas of business intelligence and competitive intelligence, requires the acquisition of decision-relevant information pieces like market trends, fusions and company values. This information is extracted by pre-processing and querying multiple sources, combining and condensing the findings. It is characteristic that the extraction process is resource intensive and has to be performed regularly and quite frequently. In the research project PARMENIDES, we are developing methods that establish ontologies over an application domain, annotate documents with the ontology components and identify the entities in them, so that we can decompose business into conventional queries towards entities and XML-annotated texts.

AB - Strategic decision making, especially in the areas of business intelligence and competitive intelligence, requires the acquisition of decision-relevant information pieces like market trends, fusions and company values. This information is extracted by pre-processing and querying multiple sources, combining and condensing the findings. It is characteristic that the extraction process is resource intensive and has to be performed regularly and quite frequently. In the research project PARMENIDES, we are developing methods that establish ontologies over an application domain, annotate documents with the ontology components and identify the entities in them, so that we can decompose business into conventional queries towards entities and XML-annotated texts.

KW - information extraction

KW - text mining

KW - ontologies

KW - business intelligence

KW - competitive intelligence

M3 - Conference contribution

SN - 2905450096

SP - 156

EP - 169

BT - Proceedings of RIAO '04

PB - Centre de hautes études internationales d'informatique documentaire

CY - Paris

ER -

Coupling information extraction and data mining for ontology learning in PARMENIDES

Abstract

Keywords

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