LENN: Laplacian Probability Based Extended Nearest Neighbor Classification Algorithm for Web Page Retrieval

Title

LENN: Laplacian Probability Based Extended Nearest Neighbor Classification Algorithm for Web Page Retrieval

Creator

Vijaya P.; Chander S.; Raju G.

Description

Web page prediction is the area of interest that enables to tackle the problem of dealing with the massive collection of the web pages, mainly, in retrieving the highly relevant web pages. The hectic challenge of the web page prediction methods relied on time-effective and cost-effective management. The problem of dealing with the issue is tackled using the efficient web page retrieval algorithm. The paper proposes a new classifier called, Laplacian probability based Extended Nearest Neighbor (LENN)that is formed through the integration of the Laplacian probability with the Extended Nearest Neighbor (ENN)classifier. The proposed LENN classifier determines the nearest web pages of the query. Accordingly, the web page retrieval is done in three important steps, such as pre-processing, feature indexing and web page retrieval. The key words are stored in the database for performing the feature match such that the highly relevant web page is retrieved based on the maximum value of the score. The experimentation using five benchmarks prove that the proposed method is effective compared with the existing methods of web page retrieval. The maximum precision, recall, and F-measure of the proposed method is found to be 98%, 96.7%, and 97.3%, respectively. 2019 IEEE.

Source

2019 International Conference on Data Science and Communication, IconDSC 2019

Date

2019-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Extended Nearest Neighbour; Laplacian probability; stemming algorithm; stop word removal; web page retrieval

Coverage

Vijaya P., Waljat College of Applied Sciences, Muscat, Oman; Chander S., Waljat College of Applied Sciences, Muscat, Oman; Raju G., Department of CSE, Faculty of Engineering, Christ, Deemed to be University, Bengaluru, Karnataka, India

Rights

Restricted Access

Relation

ISBN: 978-153869319-3

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/IconDSC.2019.8816954

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072781806&doi=10.1109%2fIconDSC.2019.8816954&partnerID=40&md5=100b1703078d7f473bcf922147a81672