NDLI: Identifying spam tags by mining tag semantics

Content Provider	IEEE Xplore Digital Library
Author	Yang, Hsin-Chang Lee, Chung-Hong
Copyright Year	2011
Description	Author affiliation: National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan (Lee, Chung-Hong) \|\| National University of Kaohsiung, Kaohsiung, Taiwan (Yang, Hsin-Chang)
Abstract	Social bookmarking or tagging Web sites, or folk-sonomies, emerge recently since the result of traditional context-driven search of Web pages could be improved by user-annotated tags. People could retrieve, organize, and comprehend Web pages thorough such tags. However, spam tags were significantly increased and deteriorated the effectiveness of social tagging. Tags unrelated to the content of the annotated Web pages were added intentionally to improperly manipulate the ranking or retrieval result for malicious purposes. Therefore approaches for filtering and identifying spams in various granularity were proposed to conquer such deficiency. Traditional approaches most focused on user-level detection which tries to differentiate spammers from normal annotators. Such approaches may suffer from the fact that misclassification of spammers as well as spam tags often happens since the intention and behavior of spammers change dynamically. It will be better if we can detect spams in much precise ways such as individual posts or tags. In this work we propose a scheme to identify individual tag spams according to the semantic relatedness between a tag and its annotated page. We first cluster Web pages and tags separately to reveal the relationships among pages and tags, respectively. A relationship discovery process was then applied to find the relationships between a page cluster and a tag cluster. We also devised a measurement to measure the semantic relatedness between individual tag and page. Individual spam tags were then identified according to such relatedness. We conducted experiments on ECML/PKDD RSDC 2008 dataset and obtained promising result.
Sponsorship	IEEE
Starting Page	263
Ending Page	268
File Size	72185
Page Count	6
File Format	PDF
ISBN	9781467302319
e-ISBN	9788988678497
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	AICIT
Subject Keyword	Filtering Web pages Unsolicited electronic mail Tagging
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

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