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1,257
Bike: Bilingual Keyphrase Experiments
"... Abstract: This paper presents a novel strategy for translating lists of keyphrases. Typical keyphrase lists appear in scientific articles, information retrieval systems and web page meta-data. Our system combines a statistical translation model trained on a bilingual corpus of scientific papers with ..."
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Abstract: This paper presents a novel strategy for translating lists of keyphrases. Typical keyphrase lists appear in scientific articles, information retrieval systems and web page meta-data. Our system combines a statistical translation model trained on a bilingual corpus of scientific papers
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 ..."
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Cited by 213 (3 self)
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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
One sense per discourse
- In DARPA Speech and Natural Language Workshop
, 1992
"... It is well-known that there are polysemous words like sentence whose "meaning " or "sense " depends on the context of use. We have recently reported on two new word-sense disambiguation systems, one trained on bilingual material (the Canadian Hansards) and the other trained on mo ..."
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Cited by 263 (7 self)
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It is well-known that there are polysemous words like sentence whose "meaning " or "sense " depends on the context of use. We have recently reported on two new word-sense disambiguation systems, one trained on bilingual material (the Canadian Hansards) and the other trained
DKPro Keyphrases: Flexible and Reusable Keyphrase Extraction Experiments
"... DKPro Keyphrases is a keyphrase extrac-tion 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 ..."
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DKPro Keyphrases is a keyphrase extrac-tion 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
Learning to Extract Keyphrases from Text
, 1999
"... Many academic journals ask their authors to provide a list of about five to fifteen key words, 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 surprisingly wide variety of tasks for which keyphra ..."
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Cited by 71 (4 self)
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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 of experiments applies the C4.5 decision tree induction algorithm to this learning task. The second set of experiments applies
Coherent keyphrase extraction via web mining
- In Proceedings of IJCAI
, 2003
"... Keyphrases are useful for a variety of purposes, including summarizing, indexing, labeling, categorizing, clustering, highlighting, browsing, and searching. The task of automatic keyphrase extraction is to select keyphrases from within the text of a given document. Automatic keyphrase extraction mak ..."
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Cited by 76 (1 self)
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the degree of statistical association among candidate keyphrases as evidence that they may be semantically related. The statistical association is measured using web mining. Experiments demonstrate that the enhancements improve the quality of the extracted keyphrases. Furthermore, the enhancements
Using Noun Phrase Heads to Extract Document Keyphrases
, 2000
"... Automatically extracting keyphrases from documents is a task with many applications in information retrieval and natural language processing. Document retrieval can be biased towards documents containing relevant keyphrases; documents can be classified or categorized based on their keyphrases; a ..."
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Cited by 75 (0 self)
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text using a base noun phrase skimmer and an off-the-shelf online dictionary. Experiments involving human judges reveal several interesting results: the simple noun phrase-based system performs roughly as well as a state-of-the-art, corpus-trained keyphrase extractor; ratings for individual
Topical Keyphrase Extraction from Twitter
"... Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both ..."
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both relevance and interestingness of keyphrases for keyphrase ranking. We evaluate our proposed methods on a large Twitter data set. Experiments show that these methods are very effective for topical keyphrase extraction. 1
Keyphrase extraction using semantic networks structure analysis
- In Proc. of the ICDM’06
, 2006
"... Keyphrases play a key role in text indexing, summarization, and categorization. However, most of the existing keyphrase extraction approaches require human-labeled training sets. In this paper, we propose an automatic keyphrase extraction algorithm using two novel feature weights, which can be used ..."
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Cited by 12 (3 self)
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in both supervised and unsupervised tasks. This algorithm treats each document as a semantic network that holds both syntactic and statistical information. Structural dynamics of these networks can easily identify key nodes, which can be used to extract keyphrases unsupervisedly. Experiments demonstrate
Kore: keyphrase overlap relatedness for entity disambiguation
- In Proceedings of the 21st ACM CIKM
, 2012
"... Measuring the semantic relatedness between two entities is the basis for numerous tasks in IR, NLP, and Web-based knowledge extraction. This paper focuses on disambiguating names in a Web or text document by jointly mapping all names onto semantically related entities registered in a knowledge base. ..."
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Cited by 14 (2 self)
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. To this end, we have developed a novel notion of semantic relatedness between two entities represented as sets of weighted (multi-word) keyphrases, with consideration of partially overlapping phrases. This measure improves the quality of prior link-based models, and also eliminates the need for (usually
Results 1 - 10
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