The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
KEA: practical automatic keyphrase extraction
Proceedings of the fourth ACM conference on Digital libraries
Finding topic words for hierarchical summarization
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Using Noun Phrase Heads to Extract Document Keyphrases
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Domain-independent automatic keyphrase indexing with small training sets
Journal of the American Society for Information Science and Technology
Domain-specific keyphrase extraction
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
SemEval-2010 task 5: Automatic keyphrase extraction from scientific articles
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
MFSRank: an unsupervised method to extract keyphrases using semantic information
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Automatic keyphrase extraction from scientific articles
Language Resources and Evaluation
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In this paper, it is presented an unsupervised approach to automatically discover the latent keyphrases contained in scientific articles. The proposed technique is constructed on the basis of the combination of two techniques: maximal frequent sequences and pageranking. We evaluated the obtained results by using micro-averaged precision, recall and F-scores with respect to two different gold standards: 1) reader's keyphrases, and 2) a combined set of author's and reader's keyphrases. The obtained results were also compared against three different baselines: one unsupervised (TF-IDF based) and two supervised (Naïve Bayes and Maximum Entropy).