Text Keyword Extraction Based on Meta-Learning Strategy

Keyword extraction is an important content in many fields and it is a key step to achieve document retrieval, information retrieval, scientific and technological literature indexing, news reading, text clustering and classification, Machine Translation and so on. In order to improved the accuracy of keyword extraction for text, we put forward a framework of keyword extraction based on meta-learning. This framework not only integrates the keyword extraction algorithm selection, parameter adjustment algorithm, but also integrates a variety of algorithms. Experimental results show that keyword extraction based on meta learning is not only simple, but also significantly improved the accuracy of keyword extraction.