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Mining the Web for Lexical Knowledge to Improve Keyphrase Extraction: Learning from Labeled and Unlabeled Data
[article]
2002
arXiv
pre-print
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I present experiments that show that the new features result in improved keyphrase extraction, although they are neither domain-specific nor training-intensive. ...
of training documents in the given domain, with manually assigned keyphrases). ...
GNU General Public License, and for sharing their results with me. ...
arXiv:cs/0212011v1
fatcat:23berap4sfbphaesdbnfoiepxm
KeaKAT: An Online Automatic Keyphrase Assignment Tool
2012
2012 10th International Conference on Frontiers of Information Technology
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However using Kea++ and its refinement as a system for assigning keyphrases to documents is not simple for users of a domain other than computing. The system needs to be installed and configured. ...
The extended refinement methodology was developed to fine tune the results of Kea++ for multiple domains. ...
Extraction phase uses the model to assign keyphrases to the document. Keyphrase assignment task can also be performed by Maui [13] along with keyphrase extraction and tagging. ...
doi:10.1109/fit.2012.14
dblp:conf/fit/IrfanKKA12
fatcat:3mb6qt2ehzdxncrvi4sya4ayp4
Improved Keyword and Keyphrase Extraction from Meeting Transcripts
2012
International Journal of Computer Applications
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In addition of traditional frequency or position-based clues, term specificity features, decision-making sentence-related features, as well as a group of features derived from summary sentences. ...
Identifying Keywords Using Feature Extraction
N-gram based Keyphrase Extraction Keyphrases are the combination of 2 or more words which describe a meaningful and important content in a document. ...
doi:10.5120/8260-1800
fatcat:oa6qozzoyrdt7cbxg62mbe34iq
Exploiting and Evaluating a Supervised, Multilanguage Keyphrase Extraction Pipeline for Under-Resourced Languages
2017
RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning
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This paper evaluates different techniques for building a supervised, multilanguage keyphrase extraction pipeline for languages which lack a gold standard. ...
Starting from an unsupervised English keyphrase extraction pipeline, we implement pipelines for Arabic, Italian, Portuguese, and Romanian, and we build test collections for languages which lack one. ...
Features Extraction After the identification of the candidate keyphrases we assign to each of them seven features. ...
doi:10.26615/978-954-452-049-6_012
dblp:conf/ranlp/BasaldellaHAPST17
fatcat:x5qlfaivkffvho3eapxhsxtyo4
A Review of Keyphrase Extraction
[article]
2019
arXiv
pre-print
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2019 pre-print arXiv:1905.05044v1 fatcat:oyzsocrrjndkfbeb5ilyvnvtuy
Keyphrase extraction is a textual information processing task concerned with the automatic extraction of representative and characteristic phrases from a document that express all the key aspects of its ...
This article introduces keyphrase extraction, provides a well-structured review of the existing work, offers interesting insights on the different evaluation approaches, highlights open issues and presents ...
| Keyphrase Extraction Software Both commercial and free software is developed for keyphrase extraction. ...
arXiv:1905.05044v2
fatcat:xeweqtrjrfbefi2h5g42uld4pe
Keyphrase Extraction using Sequential Labeling
[article]
2016
arXiv
pre-print
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Several unsupervised techniques and classifiers exist for extracting keyphrases from text documents. ...
In addition to a more natural modeling for the keyphrase extraction problem, we show that tagging models yield significant performance benefits over existing state-of-the-art extraction methods. ...
Ranking approaches were also investigated for keyphrase extraction for specific domains where preference information among keyphrases is available (Jiang et al., 2009) . ...
arXiv:1608.00329v2
fatcat:xjxmry4ae5eg7doek277i3dvtm
:{unav)
2012
Information retrieval (Boston)
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We developed the GenEx algorithm specifically for automatically extracting keyphrases from text. ...
We approach the problem of automatically extracting keyphrases from text as a supervised learning task. ...
Thanks to Elaine Sin of the University of Calgary for creating the keyphrases for the email message corpus. ...
doi:10.1023/a:1009976227802
fatcat:jmsmm3tgb5gh5flo6z3vcezhwa
DKPro Keyphrases: Flexible and Reusable Keyphrase Extraction Experiments
2014
Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations
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DKPro Keyphrases is a keyphrase extraction framework based on UIMA. It offers a wide range of state-of-the-art keyphrase experiments approaches. ...
At the same time, it is a workbench for developing new extraction approaches and evaluating their impact. DKPro Keyphrases is publicly available under an open-source license. ...
Although Maui provides training data along with their software, this training data is highly domain-specific. ...
doi:10.3115/v1/p14-5006
dblp:conf/acl/ErbsSGZ14
fatcat:h5pdpbd6iney5jpoppj6qhndru
Automatic keyphrase annotation of scientific documents using Wikipedia and genetic algorithms
2013
Journal of information science
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We have devised a set of twenty statistical, positional, and semantical features for candidate phrases to capture and reflect various properties of those candidates which have the highest keyphraseness ...
Topical annotation of documents with keyphrases is a proven method for revealing the subject of scientific and research documents to both human readers and information retrieval systems. ...
In some domains or datasets more general keyphrases are preferred by human annotators, whereas in others more specific keyphrases are preferred. ...
doi:10.1177/0165551512472138
fatcat:scx3iyeum5ds3onhow47uunj7i
A Distributed Framework for NLP-Based Keyword and Keyphrase Extraction From Web Pages and Documents
2015
Proceedings of the 21st International Conference on Distributed Multimedia Systems
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Each database record is populated with an extracted keyword or keyphrase, its corresponding POS-tag (or a different custom tag if it is a keyphrase), TF-IDF value and the source web domain.
IV. ...
subsequent estimation of extracted keywords/keyphrases relevance at web domain level (as later described). ...
doi:10.18293/dms2015-024
dblp:conf/dms/NesiPS15
fatcat:ieenhxagojenfdivup23wt42h4
Learning Algorithms for Keyphrase Extraction
[article]
2002
arXiv
pre-print
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We developed the GenEx algorithm specifically for automatically extracting keyphrases from text. ...
We approach the problem of automatically extracting keyphrases from text as a supervised learning task. ...
Thanks to Elaine Sin of the University of Calgary for creating the keyphrases for the email message corpus. ...
arXiv:cs/0212020v1
fatcat:figcbj33vnd2jld2m7z2i3xioy
Machine Learning Based Keyphrase Extraction: Comparing Decision Trees, Naïve Bayes, and Artificial Neural Networks
2012
Journal of Information Processing Systems
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The three machine learning based keyphrase extraction methods that we use for experimentation have been compared with a publicly available keyphrase extraction system called KEA. ...
The paper presents three machine learning based keyphrase extraction methods that respectively use Decision Trees, Naïve Bayes, and Artificial Neural Networks for keyphrase extraction. ...
They used a domain specific glossary database to determine the domain specificity of the candidate phrases and integrated the domain specific feature and the traditional term frequency feature to rank ...
doi:10.3745/jips.2012.8.4.693
fatcat:bzsl6zau45f3hcwlvbfuoz5fre
Identifying important concepts from medical documents
2006
Journal of Biomedical Informatics
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The latter assigns weights to extracted noun phrases for a medical document based on how important they are to that document and how domain specific they are in the medical domain. ...
KIP combines two functions: noun phrase extraction and keyphrase identification. The former automatically extracts noun phrases from medical literature as keyphrase candidates. ...
KIP's algorithm KIP is a domain-specific keyphrase extraction program, not a keyphrase assignment program, which means the generated keyphrases must occur in the document text. ...
doi:10.1016/j.jbi.2006.02.001
pmid:16545986
fatcat:mysdq64h55hylduaihta3lgcni
Building a Scientific Concept Hierarchy Database (SCHBase)
2015
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
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We present SCHBASE, a hierarchical database of keyphrases extracted from large collections of scientific literature. ...
Extracted keyphrases can enhance numerous applications ranging from search to tracking the evolution of scientific discourse. ...
Acknowledgments The authors thank the Microsoft Academic team, Jaime Teevan, Susan Dumais, and Carl Lagoze for providing us with data and advice. ...
doi:10.3115/v1/p15-1059
dblp:conf/acl/AdarD15
fatcat:yjyvp2wayrf3jhqd3jsiqukw6a
Representing Documents via Latent Keyphrase Inference
2016
Proceedings of the 25th International Conference on World Wide Web - WWW '16
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In this paper, we propose a data-driven model named Latent Keyphrase Inference (LAKI ) that represents documents with a vector of closely related domain keyphrases instead of single words or existing concepts ...
Compared with the state-of-art document representation approaches, LAKI fills the gap between bag-of-words and concept-based models by using domain keyphrases as the basic representation unit. ...
Extract domain keyphrases from a domain-focused document corpus; and 2. ...
doi:10.1145/2872427.2883088
pmid:28229132
pmcid:PMC5318165
dblp:conf/www/LiuRSCVH16
fatcat:7bnq3lg7areatavtfkjaw5pane
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