Arabic keyword extraction using SOM neural network

Joint Authors

Amush, Ibtihal H.
Samawi, Venus W.

Source

International Computer Sciences and Informatics Conference, Amman, Jordan 12-13 January 2016.

Publisher

Amman Arab University

Publication Date

2016-01-31

Country of Publication

Jordan

No. of Pages

10

Main Subjects

Information Technology and Computer Science

English Abstract

Keywords are considered an abridged version of the text which indicate the important information implied within the document.

The availability of huge amount of information on the WWW makes the process of analyzing document information and finding the proper keywords manually very difficult.

Therefore, automatic keyword extraction techniques (AKE) are needed.

In this paper, we will tackle the problem of automatic keyword extraction from Arabic documents base on unsupervised learning method.

The main objective of this research is to propose an automatic Arabic keyword extraction (AAKE) technique from single document using full-text based indexing.

The proper feature-set that improves AAKE performance is specified.

Self-organizing map (SOM) neural network is used as an unsupervised learning method.

The performance of the proposed technique is evaluated using recall, precision, and F-measure.

Encouraging results are obtained compared with Sakhr keyword extractor.

Data Type

Conference Papers

Record ID

BIM-767290

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