Keyword and Keyphrase Extraction Techniques: A Literature Review
Sifatullah Siddiqi,Aditi Sharan +1 more
TLDR
In this paper, a survey of various techniques available in text mining for keyword and keyphrase extraction is presented.Abstract:
In this paper we present a survey of various techniques available in text mining for keyword and keyphrase extraction.read more
Citations
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Journal ArticleDOI
Ensemble of keyword extraction methods and classifiers in text classification
TL;DR: The empirical analysis indicates that the utilization of keyword-based representation of text documents in conjunction with ensemble learning can enhance the predictive performance and scalability ofText classification schemes, which is of practical importance in the application fields of text classification.
Journal ArticleDOI
Information extraction meets the semantic web: a survey
TL;DR: Millennium Institute for Foundational Research on Data (IMFD) Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT), CONICyT FONDECYT: 1181896
Journal Article
International Encyclopedia of Information and Library Science
TL;DR: The second edition of the International Encyclopedia of Information and Library Science (IEILS) by Feather and Sturges has been substantially revised and updated to include rapid changes in technology since the first edition was published in 1997.
Posted Content
A Survey of Knowledge-Enhanced Text Generation.
TL;DR: A comprehensive review of the research on knowledge-enhanced text generation over the past five years is presented, which includes two parts: (i) general methods and architectures for integrating knowledge into text generation; (ii) specific techniques and applications according to different forms of knowledge data.
Journal ArticleDOI
TeKET : a Tree-Based Unsupervised Keyphrase Extraction Technique
Gollam Rabby,Gollam Rabby,Saiful Azad,Saiful Azad,Mufti Mahmud,Kamal Z. Zamli,Kamal Z. Zamli,Mahbubur Rahman +7 more
TL;DR: The proposed unsupervised keyphrase extraction technique, named TeKET or Tree-based Keyphrase Extraction Technique, is a domain-independent technique that employs limited statistical knowledge and requires no train data.
References
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Proceedings Article
TextRank: Bringing Order into Text
Rada Mihalcea,Paul Tarau +1 more
TL;DR: TextRank, a graph-based ranking model for text processing, is introduced and it is shown how this model can be successfully used in natural language applications.
Proceedings ArticleDOI
Improved automatic keyword extraction given more linguistic knowledge
TL;DR: By adding linguistic knowledge to the representation, rather than relying only on statistics, a better result is obtained as measured by keywords previously assigned by professional indexers, by extracting NP-chunks gives a better precision than n-grams.
Journal ArticleDOI
Learning Algorithms for Keyphrase Extraction
TL;DR: In this paper, the problem of automatically extracting keyphrases from text is treated as a supervised learning task, where the learning algorithm must learn to classify as positive or negative examples of key phrases.
Journal ArticleDOI
Technical terminology: some linguistic properties and an algorithm for identification in text
John S. Justeson,Slava M. Katz +1 more
TL;DR: This paper identifies some linguistic properties of technical terminology, and uses them to formulate an algorithm for identifying technical terms in running text, and presents a terminology indentification algorithm that is motivated by these linguistic properties.
Proceedings Article
Domain-specific keyphrase extraction
TL;DR: This paper shows that a simple procedure for keyphrase extraction based on the naive Bayes learning scheme performs comparably to the state of the art, and explains how this procedure's performance can be boosted by automatically tailoring the extraction process to the particular document collection at hand.