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pro vyhledávání: '"Automatic taxonomy induction"'
Akademický článek
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Autor:
Michelle Vanni, Zeqiu Wu, Chao Zhang, Brian M. Sadler, Dongming Lei, Jiawei Han, Xiang Ren, Jiaming Shen
Publikováno v:
KDD
Taxonomies are of great value to many knowledge-rich applications. As the manual taxonomy curation costs enormous human effects, automatic taxonomy construction is in great demand. However, most existing automatic taxonomy construction methods can on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb513ba0dad2cec5d9101074e888edfe
http://arxiv.org/abs/1910.08194
http://arxiv.org/abs/1910.08194
Autor:
Alfio Gliozzo, Md. Faisal Mahbub Chowdhury, Nandana Mihindukulasooriya, Sarthak Dash, Nicolas Rodolfo Fauceglia
Publikováno v:
EMNLP/IJCNLP (3)
Scopus-Elsevier
Scopus-Elsevier
The Knowledge Graph Induction Service (KGIS) is an end-to-end knowledge induction system. One of its main capabilities is to automatically induce taxonomies from input documents using a hybrid approach that takes advantage of linguistic patterns, sem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c6ef48f3ee5eef201e77f6cb845e8a9
https://doi.org/10.18653/v1/d19-3005
https://doi.org/10.18653/v1/d19-3005
Autor:
Matthias J. Feiler
Publikováno v:
Machine Learning and Data Mining in Pattern Recognition ISBN: 9783319961354
MLDM (1)
MLDM (1)
In this paper we develop a new algorithm for automatic taxonomy construction from a text corpus. In contrast to existing work, our objective is not to develop a general purpose lexicon or ontology but to identify the structure in a time–ordered seq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de1eda8311f869c000955a7fc691eb7b
https://doi.org/10.1007/978-3-319-96136-1_13
https://doi.org/10.1007/978-3-319-96136-1_13
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 27:1861-1874
In this paper, we study a challenging problem of deriving a taxonomy from a set of keyword phrases. A solution can benefit many real-world applications because i) keywords give users the flexibility and ease to characterize a specific domain; and ii)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc660212fe6ea69c7b45c133a4c75eed
https://doi.org/10.1109/tkde.2015.2397432
https://doi.org/10.1109/tkde.2015.2397432
Publikováno v:
WWW (Companion Volume)
Automatic taxonomy construction aims to build a categorization system without human efforts. Traditional textual pattern based methods extract hyponymy relation in raw texts. However, these methods usually yield low precision and recall. In this pape
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c6a4eceb205435e72f308d3b46c0ac4
https://doi.org/10.1145/3041021.3054235
https://doi.org/10.1145/3041021.3054235
Publikováno v:
Decision Support Systems, 62, 78-93. Elsevier
In this paper we present a framework for the automatic building of a domain taxonomy from text corpora, called Automatic Taxonomy Construction from Text (ATCT). This framework comprises four steps. First, terms are extracted from a corpus of document
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c619e3a697fde8e71b303ba8aa427414
https://doi.org/10.1016/j.dss.2014.03.006
https://doi.org/10.1016/j.dss.2014.03.006
In this paper we present two methodologies for rapidly inducing multiple subject-specific taxonomies from crawled data. The first method involves a sentence-level words co-occurrence frequency method for building the taxonomy, while the second involv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::818664eb970a342f077dd7f360deebb3
https://hal.inria.fr/hal-01334236/file/IJAI2016LM_GG_4June2016.pdf
https://hal.inria.fr/hal-01334236/file/IJAI2016LM_GG_4June2016.pdf
Autor:
Els Lefever
Publikováno v:
SemEval@NAACL-HLT
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)
This paper describes our contribution to the SemEval-2015 task 17 on “Taxonomy Extraction Evaluation”. We propose a hypernym detection system combining three modules: a lexico-syntactic pattern matcher, a morphosyntactic analyzer and a module ret
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::940ac41ceb544d61134006e47e62ed85
https://doi.org/10.18653/v1/s15-2157
https://doi.org/10.18653/v1/s15-2157
Autor:
de Knijff, J, Meijer, K (Kevin), Frasincar, Flavius, Hogenboom, Frederik, Bouguettaya, A., Hauswirth, M., Liu, L.
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642244339
WISE
Twelfth International Conference on Web Information System Engineering (WISE 2011), 6997, 241-248
WISE
Twelfth International Conference on Web Information System Engineering (WISE 2011), 6997, 241-248
In this paper, we propose the Automatic Taxonomy Construction from Text (ATCT) framework for building taxonomies from text-based Web corpora. The framework is composed of multiple processing steps. Firstly, domain terms are extracted using a filterin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdc58bd0cc9379f3af6ec2de2a1797d6
https://doi.org/10.1007/978-3-642-24434-6_18
https://doi.org/10.1007/978-3-642-24434-6_18