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Results 1 - 10
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389
Domain-specific keyphrase extraction
- PROC. SIXTEENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE
, 1999
"... Keyphrases are an important means of document summarization, clustering, and topic search. Only a small minority of documents have author-assigned keyphrases, and manually assigning keyphrases to existing documents is very laborious. Therefore it is highly desirable to automate the keyphrase extract ..."
Abstract
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Cited by 224 (17 self)
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extraction process. 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. It goes on to explain how this procedure’s performance can be boosted by automatically tailoring the extraction process to the particular
Learning Algorithms for Keyphrase Extraction
- INFORMATION RETRIEVAL
, 2000
"... Many academic journals ask their authors to provide a list of about five to fifteen keywords, to appear on the first page of each article. Since these key words are often phrases of two or more words, we prefer to call them keyphrases. There is a wide variety of tasks for which keyphrases are useful ..."
Abstract
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Cited by 213 (3 self)
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are useful, as we discuss in this paper. We approach the problem of automatically extracting keyphrases from text as a supervised learning task. We treat a document as a set of phrases, which the learning algorithm must learn to classify as positive or negative examples of keyphrases. Our first set
Keyphrase Extraction for Summarization Purposes: The
- LAKE System at DUC-2004, Document Understanding Workshop
, 2004
"... We report on ITC-irst participation at Task 1 (very short document summaries) at DUC-2004. We propose to exploit a keyphrase ex-traction methodology in order to identify rel-evant terms in the document. The LAKE al-gorithm first considers a number of linguis-tic features to extract a list of well mo ..."
Abstract
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Cited by 2 (0 self)
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We report on ITC-irst participation at Task 1 (very short document summaries) at DUC-2004. We propose to exploit a keyphrase ex-traction methodology in order to identify rel-evant terms in the document. The LAKE al-gorithm first considers a number of linguis-tic features to extract a list of well
Domain-Speci Keyphrase Extraction
- Proceedings of the 16 th International Joint Conference on Arti Intelligence (IJCAI99
, 1999
"... Keyphrases are an important means of doc-ument summarization, clustering, and topic search. Only a small minority of documents have author-assigned keyphrases, and manually assigning keyphrases to existing documents is very laborious. Therefore it is highly desirable to automate the keyphrase extrac ..."
Abstract
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Cited by 2 (1 self)
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extraction process. 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. It goes on to explain how this procedure's performance can be boosted by automatically tailoring the extraction process
Large dataset for keyphrases extraction
, 2009
"... We propose a large dataset for machine learning-based automatic keyphrase extraction. The dataset has a high quality and consist of 2,000 of scientific papers from computer science domain published by ACM. Each paper has its keyphrases assigned by the authors and verified by the reviewers. Different ..."
Abstract
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Cited by 3 (0 self)
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We propose a large dataset for machine learning-based automatic keyphrase extraction. The dataset has a high quality and consist of 2,000 of scientific papers from computer science domain published by ACM. Each paper has its keyphrases assigned by the authors and verified by the reviewers
Keyphrase extraction in scientific publications
- In Proc. of International Conference on Asian Digital Libraries (ICADL ’07
, 2007
"... Abstract. We present a keyphrase extraction algorithm for scientific publications. Different from previous work, we introduce features that capture the positions of phrases in document with respect to logical sections found in scientific discourse. We also introduce features that capture salient mor ..."
Abstract
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Cited by 30 (3 self)
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Abstract. We present a keyphrase extraction algorithm for scientific publications. Different from previous work, we introduce features that capture the positions of phrases in document with respect to logical sections found in scientific discourse. We also introduce features that capture salient
Approximate Matching for Evaluating Keyphrase Extraction
"... We propose a new evaluation strategy for keyphrase extraction based on approximate keyphrase matching. It corresponds well with human judgments and is better suited to assess the performance of keyphrase extraction approaches. Additionally, we propose a generalized framework for comprehensive analys ..."
Abstract
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Cited by 6 (0 self)
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We propose a new evaluation strategy for keyphrase extraction based on approximate keyphrase matching. It corresponds well with human judgments and is better suited to assess the performance of keyphrase extraction approaches. Additionally, we propose a generalized framework for comprehensive
Kea: Practical automatic keyphrase extraction
- IN PROCEEDINGS OF THE 4TH ACM CONFERENCE ON DIGITAL LIBRARIES
, 1998
"... Keyphrases provide semantic metadata that summarize and characterize documents. This paper describes Kea, an algorithm for automatically extracting keyphrases from text. Kea identifies candidate keyphrases using lexical methods, calculates feature values for each candidate, and uses a machine-learni ..."
Abstract
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Cited by 175 (8 self)
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Keyphrases provide semantic metadata that summarize and characterize documents. This paper describes Kea, an algorithm for automatically extracting keyphrases from text. Kea identifies candidate keyphrases using lexical methods, calculates feature values for each candidate, and uses a machine
Results 1 - 10
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389
