NDLI: Web Document Clustering by Using Automatic Keyphrase Extraction

Content Provider	IEEE Xplore Digital Library
Author	Juhyun Han Taehwan Kim Joongmin Choi
Copyright Year	2007
Description	Author affiliation: Hanyang Univ., Ansan (Juhyun Han; Taehwan Kim; Joongmin Choi)
Abstract	In most traditional techniques of document clustering, the number of total clusters is not known in advance and the cluster that contain the target information cannot be determined since the semantic nature is not associated with the cluster. The well-known K-means clustering algorithm partially solves these problems by allowing users to specify the number of clusters. However, if the pre-specified number of clusters is modified, the precision of each result also changes. To solve this problem, this paper proposes a new clustering algorithm based on the Kea keyphrase extraction algorithm which returns several keyphrases from the source documents by using some machine learning techniques. In this paper, documents are grouped into several clusters like K-means, but the number of clusters is automatically determined by the algorithm with some heuristics using the extracted keyphrases. Our Kea-means clustering algorithm provides easy and efficient ways to extract test documents from massive quantities of resources.
Starting Page	56
Ending Page	59
File Size	601978
Page Count	4
File Format	PDF
ISBN	0769530281
DOI	10.1109/WI-IATW.2007.46
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Machine learning algorithms Heuristic algorithms Conferences Clustering algorithms Machine learning Partitioning algorithms Data mining Kea-means ClusteringKeyphrasesK-meansClustering Intelligent agent Testing
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Web Document Clustering by Using Automatic Keyphrase Extraction

Web Document Clustering by Using Automatic Keyphrase Extraction

Turkish keyphrase extraction using KEA

Text mining using keyphrase extraction.

Coherent Keyphrase Extraction via Web Mining (2003)

Coherent keyphrase extraction via web mining (2003)

Improving keyphrase extraction by using document topic information

Enhancing the K-means Clustering Algorithm by Using a O(n logn) Heuristic Method for Finding Better Initial Centroids

Thesaurus based automatic keyphrase indexing

Web Document Clustering by Using Automatic Keyphrase Extraction

Similar Documents

Web Document Clustering by Using Automatic Keyphrase Extraction

Web Document Clustering by Using Automatic Keyphrase Extraction

Turkish keyphrase extraction using KEA

Text mining using keyphrase extraction.

Coherent Keyphrase Extraction via Web Mining (2003)

Coherent keyphrase extraction via web mining (2003)

Improving keyphrase extraction by using document topic information

Enhancing the K-means Clustering Algorithm by Using a O(n logn) Heuristic Method for Finding Better Initial Centroids

Thesaurus based automatic keyphrase indexing

Web Document Clustering by Using Automatic Keyphrase Extraction