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Learning Algorithms for Keyphrase Extraction [article]

Peter D. Turney
2002 arXiv   pre-print
The second set of experiments applies the GenEx algorithm to the task. 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

Kamal Sarkar, Mita Nasipuri, Suranjan Ghose
2012 Journal of Information Processing Systems  
The paper presents three machine learning based keyphrase extraction methods that respectively use Decision Trees, Naïve Bayes, and Artificial Neural Networks for keyphrase extraction.  ...  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.  ...  A FRAMEWORK FOR MACHINE LEARNING BASED KEYPHRASE EXTRACTION This section discusses a framework for keyphrase extraction using a machine learning algorithm.  ... 
doi:10.3745/jips.2012.8.4.693 fatcat:bzsl6zau45f3hcwlvbfuoz5fre

Keyphrase Extraction using supervise learning
IJARCCE - Computer and Communication Engineering

SHOBHA S. RASKAR, SALMA H. PATHAN
2014 IJARCCE  
In Kea-means algorithm, documents are clustered into several groups like K-means, but the number of clusters is determined automatically by using the extracted keyphrases.  ...  Set of training documents and machine learning is used to determine phrases are keyphrase or not.  ...  EXPERIMENT AND RESULT To extract keyphrases from documents model has to build, which can be used for the purpose of extraction, and train system from some known facts using supervised learning.  ... 
doi:10.17148/ijarcce.2014.31135 fatcat:l5mr6rbxbfg6hciqjgizm5fmgq

Extraction Of Significant Phrases From Text

Yuan J. Lui
2007 Zenodo  
Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm.  ...  machine learning method to distinguish keyphrases from non-keyphrases.  ...  ACKNOWLEDGMENT The author would like to thank his supervisors, Professor Richard Brent and Dr Ani Calinescu, for their valuable comments on his work.  ... 
doi:10.5281/zenodo.1072618 fatcat:hsldpgufvfem7kpgztjh4p26qi

Automatic Keyphrase Extraction from Medical Documents [chapter]

Kamal Sarkar
2009 Lecture Notes in Computer Science  
The proposed method has been compared to a popular keyphrase extraction algorithm, called Kea.  ...  This paper presents an automatic keyphrase extraction method based on the naive Bayesian learning that exploits a number of domain-specific features to boost up the keyphrase extraction performance in  ...  Keyphrase Identification. Training Naïve Bayesian learning algorithm for keyphrase extraction requires document noun phrases to be represented as feature vectors.  ... 
doi:10.1007/978-3-642-11164-8_44 fatcat:qw6z2hta6feytbrmv4mm4lldrm

A Hybrid of Statistical and Machine Learning Methods for Arabic Keyphrase Extraction

Nidaa Ghalib Ali, Nazlia Omar
2015 Asian Journal of Applied Sciences  
Thus, for the purpose of Arabic keyphrase extraction, this study recommends a hybrid approach which involves the merger of statistical and machine learning methods.  ...  A wide range of techniques have been generated over time for the purpose of keyphrase extraction and much emphasis has been placed on the automatic extraction of keyphrases involving manuscripts in English  ...  The purpose of this study was to recommend ways of utilizing the results from a number of keyphrase extraction methods as input features meant for a machine learning algorithm.  ... 
doi:10.3923/ajaps.2015.269.276 fatcat:rbjimk7zcfhajc7il5qeabhrde

Turkish keyphrase extraction using KEA

Nagehan Pala, Ilyas Cicekli
2007 2007 22nd international symposium on computer and information sciences  
In this paper, we present implementation of Keyphrase Extraction Algorithm (KEA) for Turkish as well as extending it with new features to improve its performance.  ...  Assigning keyphrases to these documents manually is a tedious process and requires knowledge of the subject. Automatic Keyphrase Extraction solves this problem.  ...  KEA: KEYPHRASE EXTRACTION ALGORITHM KEA algorithm uses a supervised learning algorithm, so it has two stages: 1) Training Stage: KEA takes the training data and creates a model which is used to extract  ... 
doi:10.1109/iscis.2007.4456860 fatcat:isrxhi3wn5fm7p3ugoinbznbqe

Domain-Specific Keyphrase Extraction

Eibe Frank, Gordon W. Paynter, Ian H. Witten, Carl Gutwin, Craig G. Nevill-Manning
1999 International Joint Conference on Artificial Intelligence  
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.  ...  Therefore it is highly desirable to automate the keyphrase extraction process.  ...  In con-trast to GenEx, however, it does not employ a specialpurpose genetic algorithm for training and keyphrase extraction: it is based on the well-known naive Bayes machine learning technique.  ... 
dblp:conf/ijcai/FrankPWGN99 fatcat:utfxspupsfdl5opeoqrrb6c6ia

:{unav)

Peter D. Turney
2012 Information retrieval (Boston)  
The second set of experiments applies the GenEx algorithm to the task. 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

Document Specific Supervised Keyphrase Extraction with Strong Semantic Relations

Huiting Liu, Lili Wang, Peng Zhao, Xindong Wu
2019 IEEE Access  
In this paper, a keyphrase extraction algorithm using maximum sequential pattern mining with one-off and general gaps condition, called Ke-MSMING, is presented.  ...  keyphrase extraction.  ...  Qingren Wang for assisting us with the experiment setting up.  ... 
doi:10.1109/access.2019.2948891 fatcat:h57usmel3jamvewrnb6rsdxbme

Semi-Supervised Learning for Neural Keyphrase Generation [article]

Hai Ye, Lu Wang
2019 arXiv   pre-print
First, unlabeled documents are first tagged with synthetic keyphrases obtained from unsupervised keyphrase extraction methods or a selflearning algorithm, and then combined with labeled samples for training  ...  In this paper, we propose semi-supervised keyphrase generation methods by leveraging both labeled data and large-scale unlabeled samples for learning. Two strategies are proposed.  ...  We thank three anonymous reviewers for their insightful suggestions on various aspects of this work.  ... 
arXiv:1808.06773v2 fatcat:pogfnhnyfvfy3bu5gbbl52mxau

Locating knowledge sources through keyphrase extraction

Sara Tedmori, Thomas W. Jackson, Dino Bouchlaghem
2006 Knowledge and Process Management  
In this paper, the authors present an automated process for keyphrase extraction from email messages.  ...  There are a large number of tasks for which keyphrases can be useful.  ...  KEYPHRASE EXTRACTION FROM EMAIL MESSAGES This section describes a keyphrase extraction algorithm for email text.  ... 
doi:10.1002/kpm.250 fatcat:xtxsg3ov7jf3hbblh5gypi2cxq

KIP: a keyphrase identification program with learning functions

Y.B. Wu, Q. Li, R.S. Bot, X. Chen
2004 International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004.  
KIP first populates its database using manually identified keyphrases; each keyphrase is preprocessed and assigned an initial weight. It then extracts noun phrases from documents.  ...  In this paper, we report a keyphrase identification program (KIP) which uses sample human keyphrases and then learns to identify additional new keyphrases.  ...  Conclusion In this paper, we have introduced and evaluated a new algorithm, KIP, for automatically extracting keyphrase from documents.  ... 
doi:10.1109/itcc.2004.1286694 dblp:conf/itcc/WuLBC04 fatcat:iaial6ubybcqxkelaglcuceafa

Improving the Performance of Adopted Approaches for Extracting Arabic Keyphrases

Fatma Elghannam
2016 International Journal of Computer Applications  
In this work the improvement of automatic keyphrases extraction using deep linguistic features and supervised machine learning algorithm is discussed.  ...  The n-gram method for extracting important keyphrases produces huge number of candidate terms.  ...  The Keyphrase Extraction Algorithm KEA [6] , [16] , [17] uses the machine learning techniques and Naive Bayes algorithm to classify the candidate phrases as keyphrases or not.  ... 
doi:10.5120/ijca2016912099 fatcat:2mhccgaeifbpxer2ro25z4mx5i

Keyphrase extraction through query performance prediction

Gonenc Ercan, Ilyas Cicekli
2012 Journal of information science  
In this vein, we start off with the introduction of the related works on keyphrase extraction. Following this, in Section 3 we give the details of our algorithm.  ...  This work contributes to keyphrase extraction literature by showing that methods used in QPP improve keyphrase extraction.  ...  Our keyphrase extraction algorithm is a supervised learning algorithm that uses QPP features.  ... 
doi:10.1177/0165551512448984 fatcat:xyjh537rinbfjokc6liq44vqoe
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