@inproceedings{saetre-etal-2008-connecting,
title = "Connecting Text Mining and Pathways using the {P}ath{T}ext Resource",
author = "S{\ae}tre, Rune and
Kemper, Brian and
Oda, Kanae and
Okazaki, Naoaki and
Matsuoka, Yukiko and
Kikuchi, Norihiro and
Kitano, Hiroaki and
Tsuruoka, Yoshimasa and
Ananiadou, Sophia and
Tsujii, Jun{'}ichi",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Tapias, Daniel",
booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)",
month = may,
year = "2008",
address = "Marrakech, Morocco",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2008/pdf/442_paper.pdf",
abstract = "Many systems have been developed in the past few years to assist researchers in the discovery of knowledge published as English text, for example in the PubMed database. At the same time, higher level collective knowledge is often published using a graphical notation representing all the entities in a pathway and their interactions. We believe that these pathway visualizations could serve as an effective user interface for knowledge discovery if they can be linked to the text in publications. Since the graphical elements in a Pathway are of a very different nature than their corresponding descriptions in English text, we developed a prototype system called PathText. The goal of PathText is to serve as a bridge between these two different representations. In this paper, we first describe the overall architecture and the interfaces of the PathText system, and then provide some details about the core Text Mining components.",
}
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<abstract>Many systems have been developed in the past few years to assist researchers in the discovery of knowledge published as English text, for example in the PubMed database. At the same time, higher level collective knowledge is often published using a graphical notation representing all the entities in a pathway and their interactions. We believe that these pathway visualizations could serve as an effective user interface for knowledge discovery if they can be linked to the text in publications. Since the graphical elements in a Pathway are of a very different nature than their corresponding descriptions in English text, we developed a prototype system called PathText. The goal of PathText is to serve as a bridge between these two different representations. In this paper, we first describe the overall architecture and the interfaces of the PathText system, and then provide some details about the core Text Mining components.</abstract>
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%0 Conference Proceedings
%T Connecting Text Mining and Pathways using the PathText Resource
%A Sætre, Rune
%A Kemper, Brian
%A Oda, Kanae
%A Okazaki, Naoaki
%A Matsuoka, Yukiko
%A Kikuchi, Norihiro
%A Kitano, Hiroaki
%A Tsuruoka, Yoshimasa
%A Ananiadou, Sophia
%A Tsujii, Jun’ichi
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Tapias, Daniel
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 May
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F saetre-etal-2008-connecting
%X Many systems have been developed in the past few years to assist researchers in the discovery of knowledge published as English text, for example in the PubMed database. At the same time, higher level collective knowledge is often published using a graphical notation representing all the entities in a pathway and their interactions. We believe that these pathway visualizations could serve as an effective user interface for knowledge discovery if they can be linked to the text in publications. Since the graphical elements in a Pathway are of a very different nature than their corresponding descriptions in English text, we developed a prototype system called PathText. The goal of PathText is to serve as a bridge between these two different representations. In this paper, we first describe the overall architecture and the interfaces of the PathText system, and then provide some details about the core Text Mining components.
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/442_paper.pdf
Markdown (Informal)
[Connecting Text Mining and Pathways using the PathText Resource](http://www.lrec-conf.org/proceedings/lrec2008/pdf/442_paper.pdf) (Sætre et al., LREC 2008)
ACL
- Rune Sætre, Brian Kemper, Kanae Oda, Naoaki Okazaki, Yukiko Matsuoka, Norihiro Kikuchi, Hiroaki Kitano, Yoshimasa Tsuruoka, Sophia Ananiadou, and Jun’ichi Tsujii. 2008. Connecting Text Mining and Pathways using the PathText Resource. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).