Automatic keyphrase extraction: An overview of the state of the art
| Autor: | Brahim Ouhbi, Bouchra Frikh, Zakariae Alami Merrouni |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Information retrieval
Ontology learning business.industry Computer science InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Feature extraction 02 engineering and technology computer.software_genre Automatic summarization Task (project management) Variety (cybernetics) Support vector machine Automatic indexing 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Cluster analysis business computer Natural language processing |
| Zdroj: | CIST |
| DOI: | 10.1109/cist.2016.7805062 |
| Popis: | Keyphrases are useful for a variety of tasks in information retrieval systems and natural language processing, such as text summarization, automatic indexing, clustering/classification, ontology learning and building and conceptualizing particular knowledge domains, etc. However, assigning these keyphrases manually is time consuming and expensive in term of human resources. Therefore, there is a need to automate the task of extracting keyphrases. A wide range of techniques of keyphrase extraction have been proposed, but they are still suffering from the low accuracy rate and poor performance. This paper presents a state of the art of automatic keyphrase extraction approaches to identify their strengths and weaknesses. We also discuss why some techniques perform better than others and how can we improve the task of automatic keyphrase extraction. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|