@inproceedings{he-etal-2014-construction,
title = "Construction of Diachronic Ontologies from People{'}s Daily of Fifty Years",
author = "He, Shaoda and
Zou, Xiaojun and
Xiao, Liumingjing and
Hu, Junfeng",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/337_Paper.pdf",
pages = "3258--3263",
abstract = "This paper presents an Ontology Learning From Text (OLFT) method follows the well-known OLFT cake layer framework. Based on the distributional similarity, the proposed method generates multi-level ontologies from comparatively small corpora with the aid of HITS algorithm. Currently, this method covers terms extraction, synonyms recognition, concepts discovery and concepts hierarchical clustering. Among them, both concepts discovery and concepts hierarchical clustering are aided by the HITS authority, which is obtained from the HITS algorithm by an iteratively recommended way. With this method, a set of diachronic ontologies is constructed for each year based on People{'}s Daily corpora of fifty years (i.e., from 1947 to 1996). Preliminary experiments show that our algorithm outperforms the Google{'}s RNN and K-means based algorithm in both concepts discovery and concepts hierarchical clustering.",
}
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<abstract>This paper presents an Ontology Learning From Text (OLFT) method follows the well-known OLFT cake layer framework. Based on the distributional similarity, the proposed method generates multi-level ontologies from comparatively small corpora with the aid of HITS algorithm. Currently, this method covers terms extraction, synonyms recognition, concepts discovery and concepts hierarchical clustering. Among them, both concepts discovery and concepts hierarchical clustering are aided by the HITS authority, which is obtained from the HITS algorithm by an iteratively recommended way. With this method, a set of diachronic ontologies is constructed for each year based on People’s Daily corpora of fifty years (i.e., from 1947 to 1996). Preliminary experiments show that our algorithm outperforms the Google’s RNN and K-means based algorithm in both concepts discovery and concepts hierarchical clustering.</abstract>
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%0 Conference Proceedings
%T Construction of Diachronic Ontologies from People’s Daily of Fifty Years
%A He, Shaoda
%A Zou, Xiaojun
%A Xiao, Liumingjing
%A Hu, Junfeng
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F he-etal-2014-construction
%X This paper presents an Ontology Learning From Text (OLFT) method follows the well-known OLFT cake layer framework. Based on the distributional similarity, the proposed method generates multi-level ontologies from comparatively small corpora with the aid of HITS algorithm. Currently, this method covers terms extraction, synonyms recognition, concepts discovery and concepts hierarchical clustering. Among them, both concepts discovery and concepts hierarchical clustering are aided by the HITS authority, which is obtained from the HITS algorithm by an iteratively recommended way. With this method, a set of diachronic ontologies is constructed for each year based on People’s Daily corpora of fifty years (i.e., from 1947 to 1996). Preliminary experiments show that our algorithm outperforms the Google’s RNN and K-means based algorithm in both concepts discovery and concepts hierarchical clustering.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/337_Paper.pdf
%P 3258-3263
Markdown (Informal)
[Construction of Diachronic Ontologies from People’s Daily of Fifty Years](http://www.lrec-conf.org/proceedings/lrec2014/pdf/337_Paper.pdf) (He et al., LREC 2014)
ACL