KP-Miner: A Simple System for Effective Keyphrase Extraction

Author

El-Beltagy, Samhaa R.

Author_Institution

Dept. of Comput. Sci., Cairo Univ.

fYear

2006

fDate

Nov. 2006

Firstpage

1

Lastpage

5

Abstract

Automatic key phrase extraction has many important applications including but not limited to summarization, cataloging/indexing, feature extraction for clustering and classification, and data mining. This paper presents a simple, yet effective algorithm (KP-Miner) for achieving this task. The result of an experiment carried out to investigate the effectiveness of this algorithm is also presented. In this experiment the devised algorithm is applied to six different datasets consisting of 481 documents. The results are then compared to two existing sophisticated machine learning based automatic keyphrase extraction systems. The results of this experiment show that the devised algorithm is comparable to both systems

Keywords

data mining; learning (artificial intelligence); KP-Miner; automatic key phrase extraction; cataloging; data mining; feature extraction; indexing; machine learning; summarization; Application software; Clustering algorithms; Computer science; Data mining; Feature extraction; Humans; Indexing; Machine learning; Machine learning algorithms; Power system modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovations in Information Technology, 2006

Conference_Location

Dubai

Print_ISBN

1-4244-0674-9

Electronic_ISBN

1-4244-0674-9

Type

conf

DOI

10.1109/INNOVATIONS.2006.301948

Filename

4085463