KEA: practical automatic keyphrase extraction
Proceedings of the fourth ACM conference on Digital libraries
Learning Algorithms for Keyphrase Extraction
Information Retrieval
Thesaurus based automatic keyphrase indexing
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
Automatic keyphrase extraction from scientific documents using N-gram filtration technique
Proceedings of the eighth ACM symposium on Document engineering
KP-Miner: A keyphrase extraction system for English and Arabic documents
Information Systems
Coherent keyphrase extraction via web mining
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Conundrums in unsupervised keyphrase extraction: making sense of the state-of-the-art
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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In this paper, we develop and evaluate an automatic keyphrase extraction technique for scientific documents. A new candidate phrase generation method is proposed based on the core word expansion algorithm, which can reduce the size of candidate set by about 75% without increasing the computational complexity. Then in the step of feature calculation, when a phrase and its sub-phrases coexist as candidates, an inverse document frequency related feature is introduced for selecting the proper granularity. Experimental results show the efficiency and effectiveness of the refined candidate set and demonstrate that the overall performance of our system compares favorably with other known keyphrase extraction systems.