International Journal of Computational Intelligence Systems

Volume 7, Issue 4, August 2014, Pages 650 - 659

An Approach to Enhance the Quality of Recommendation Using Collaborative Tagging

Authors
Latha Banda, K.K. Bharadwaj
Corresponding Author
Latha Banda
Available Online 9 January 2017.
DOI
https://doi.org/10.1080/18756891.2014.960225How to use a DOI?
Keywords
Page recommendation, fuzzy classifier, Collaborative labeling, Rule generation
Abstract
Collaborative labeling portrays the process by which numerous users put in metadata in the form of keywords to shared data. Nowadays, collaborative labeling has grown in reputation on the web, on sites that permit users to label bookmarks, photographs and other details. It has been recently become useful and well known as one effective way of classifying items for future search, sharing information, and filtering. So, as to predict the future search of users, we propose a novel collaborative tagging-based page recommendation algorithm using fuzzy classifier. The method consists of three phases: Grouping, Rule Generation Phase and Page Recommendation Phase. In the proposed method, we calculate the resemblance of users in selecting tags and thereby, calculate the nearest neighbors of each user and cluster them. Then, the priority of tags and items for each user is calculated for constructing a Nominal Label Matrix and Nominal Page Matrix. Finally, the fuzzy rules are generated for page recommendation. The experimentation is carried out on delicious datasets and the experimental results ensured that the proposed algorithm has achieved the maximum hit ratio of 6.6% for neighborhood size of 20, which is higher than the existing technique which obtained only 5.5%.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
7 - 4
Pages
650 - 659
Publication Date
2017/01
ISSN
1875-6883
DOI
https://doi.org/10.1080/18756891.2014.960225How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Latha Banda
AU  - K.K. Bharadwaj
PY  - 2017
DA  - 2017/01
TI  - An Approach to Enhance the Quality of Recommendation Using Collaborative Tagging
JO  - International Journal of Computational Intelligence Systems
SP  - 650
EP  - 659
VL  - 7
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2014.960225
DO  - https://doi.org/10.1080/18756891.2014.960225
ID  - Banda2017
ER  -