Title :
Automatic keyphrases extraction from document using backpropagation
Author :
Wang, Jia-bing ; Peng, Hong ; Hu, Jing-song
Author_Institution :
Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
Automatic keyphrase extraction from documents is a task with many applications in information retrieval and natural language processing. Previously, Several keyphrase extraction methods have been proposed based on different techniques. In this paper a keyphrase extraction approach based on backpropagation is proposed. In order to determine whether a phrase is a keyphrase or not, the following features of a phrase in a given document are adopted: its term frequency TF and inverted document frequency IDF, whether or not it appears in the title or headings (subheadings) of the given document, and its distribution in the paragraphs of the given document. The algorithm is evaluated by the standard information retrieval metrics of precision and recall and human assessment. Experiment results show that this approach is competitive with other known methods.
Keywords :
backpropagation; feedforward neural nets; indexing; information retrieval; multilayer perceptrons; automatic document keyphrase extraction; backpropagation; information retrieval; multilayer feed-forward neural network; natural language processing; Application software; Backpropagation algorithms; Computer science; Data mining; Databases; Frequency measurement; Humans; Information retrieval; Natural language processing; Particle measurements; Keyphrase extraction; backpropagation; information retrieval; natural language processing;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527596