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2015 Volume 30
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RESEARCH ARTICLE   Open Access    

Quality-protected folksonomy maintenance approaches: a brief survey

  • Department of Computer Science

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  • Abstract: Folksonomy gives liberty to its users to freely assign chosen keywords as tags, and this is the main reason behind its popularity. Apart from freedom, this system also reflects the collective intelligence of the crowd. However, this freedom and liberty can degrade quality of the folksonomy. It is required that quality of the folksonomy must remain consistently excellent and does not degrade with the passage of time. This is a survey paper, in which we present a brief survey of the research efforts intended to maintain a quality-protected folksonomy. We have organized our paper by looking at the problem from four aspects namely selection of quality tags, tag management features provided by folksonomy applications, folksonomy cleaning and interoperability of tags across platforms. We conclude our review with some of the interesting research topics, which need to be explored further. Our conclusion will be relevant and beneficial for engineers and designers who aim to design and maintain a quality-protected folksonomy.
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  • Abbasi R.2011. Query expansion in folksonomies. In Proceedings of the 5th International Conference on Semantic and Digital Media Technologies (SAMT10), 1–16.

    Google Scholar

    Abel F., Henze N. & Krause D.2008. Ranking in folksonomy systems: can context help? In Proceedings of the 17th ACM Conference on Information and Knowledge Management, 1429–1430. ACM.

    Google Scholar

    Abel F., Kawase R. & Krause D.2010. Leveraging multi-faceted tagging to improve search in folksonomy systems. In Proceedings of the 21st ACM Conference on Hypertext and Hypermedia, 299–300.

    Google Scholar

    Al-Khalifa H. & Davis H.2006. Measuring the semantic value of folksonomies. Innovations in Information Technology, 2006, 1–5. IEEE. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4085397.

    Google Scholar

    Al-Khalifa H. & Davis H.2007. Towards better understanding of folksonomic patterns. In Proceedings of the 18th Conference on Hypertext and Hypermedia, 163–166. ACM Press. http://portal.acm.org/citation.cfm?doid=1286240.1286288.

    Google Scholar

    Asch S. & Solomon E.1956. Studies of independence and conformity: a minority of one against a unanimous majority. Psychological Monographs: General and Applied70(9), 1–70.

    Google Scholar

    Astrain J. A., Echarte F., Crdoba A. & Villadangos J.2009. A tag clustering method to deal with syntactic variations on collaborative social networks. In ICWE 2009, LNCS 5648, 434–441. Springer-Verlag Berlin Heidelberg. http://link.springer.com/chapter/10.1007/978-3-642-02818-2_35.

    Google Scholar

    Bartolini I., Patella M. & Romani C.2013. SHIATSU: tagging and retrieving videos without worries. Multimedia Tools and Applications63(2), 357–385.

    Google Scholar

    Baxter M.2009. Reflections from the river—singular plural. http://www.reflectionsfromtheriver.com/tag/singular-plural/.

    Google Scholar

    Benz D. & Christian K.2011. One tag to bind them all: measuring term abstractness in social metadata. In ESWC 2011, Part II, LNCS 6644, 360–374. Springer-Verlag Berlin Heidelberg.

    Google Scholar

    Catarino M. & Baptista A.2010. Relating folksonomies with Dublin Core. International Journal of Metadata, Semantics and Ontologies5(4), 285–295.

    Google Scholar

    Cattuto C., Baldassarri A., Servedio V. D. P. & Loreto V.2007. Vocabulary growth in collaborative tagging systems. CoRR abs/0704.3316. http://arxiv.org/abs/0704.3316.

    Google Scholar

    Cena F., Carmagnola F. & Cortassa O.2008. Tag interoperability in cultural web-based applications. In Proceedings of the 19th ACM Conference on Hypertext and Hypermedia (HT08), 221–222. http://dl.acm.org/citation.cfm?id=1379135.

    Google Scholar

    Chen J., Feng S. & Liu J.2014. Topic sense induction from social tags based on non-negative matrix factorization. Information Sciences280, 16–25.

    Google Scholar

    Choi Y. & Street E. D.2009. Bringing a more accurate user’s perspective into web navigation: facet analysis of folksonomy tags. iConference 2009, University of North Carolina at Chapel Hill.

    Google Scholar

    Chow K. O., Fan K. Y. K., Chan A. Y. K. & Wong G. T. L.2009. Content-based tag generation for the grouping of tags. In International Conference on Mobile, Hybrid, and On-line Learning, 7–12. http://www.computer.org/csdl/proceedings/elml/2009/3528/00/3528a007-abs.html.

    Google Scholar

    Common tag2014. Common tag. http://www.commontag.org/home.

    Google Scholar

    Cui B., Han Q., Yao J., Zhang C. & Zhou Y.2011. Modeling user expertise in folksonomies by fusing multi-type features. In Proceedings of the 16th International Conference on Database Systems for Advanced Applications, 53–67.

    Google Scholar

    Daglas S., Kakali C. & Kakavoulis D.2012. A methodology for folksonomy evaluation. In Theory and Practice of Digital Libraries (TPDL 2012), LNCS 7489, 247–259. Springer-Verlag Berlin Heidelberg. http://link.springer.com/chapter/10.1007/978-3-642-33290-6_27.

    Google Scholar

    Damme C. V., Christiaens S. & Trog D.2008. Methodological approach to determine appropriately annotated resources in narrow folksonomies. In On the Move to Meaningful Internet Systems: OTM 2008 Workshops, Meersman, R., Tari, Z. & Herrero, P. (eds). Springer-Verlag Berlin Heidelberg, 230–237.

    Google Scholar

    Damme V. D., Hepp M. & Coenen T.2008. Quality metrics for tags of broad folksonomies. In Proceedings of International Conference on Semantic Systems (I-semantics 08), Journal of Universal Computer Science (J.UCS), 118–125.

    Google Scholar

    Dang V. & Croft W. B.2010. Query reformulation using anchor text. In Proceedings of the 3rd ACM International Conference on Web Search and Data Mining, 41–50.

    Google Scholar

    Dattolo A., Ferrara F. & Tasso C.2010. The role of tags for recommendation: a survey. In 3rd International Conference on Human System Interaction, 548–555. IEEE. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5514515.

    Google Scholar

    Dattolo A. & Pitassi E.2011. Visualizing and managing folksonomies. In Proceedings of the Workshop on Semantic Adaptive Social Web (SASWeb 2011), CEUR Workshop Proceedings730, 6–14. http://www.academia.edu/2971660/Visualizing_and_Managing_Folksonomies.

    Google Scholar

    Dellschaft K. & Szomszor M.2009. Sense aware searching and exploration with MyTag. In The 8th International Semantic Web Conference (ISWC 2009), 6–7.

    Google Scholar

    Diaz J. & Tory M.2009. An exploratory study of tag-based visual interfaces for searching folksonomies. In Proceedings of the 23rd British HCI Group Annual Conference on People and Computers: Celebrating People and Technology, 410–417.

    Google Scholar

    Ding Y., Jacob E. & Fried M.2010. Upper tag ontology for integrating social tagging data. Journal of the American Society for Information Science and Technology61(3), 505–521.

    Google Scholar

    Donghee Y. & Yongmoo S.2010. User-categorized tags to build a structured folksonomy. In Second International Conference on Communication Software and Networks (ICCSN’10), 160–164.

    Google Scholar

    Dotsika F.2009. Uniting formal and informal descriptive power: reconciling ontologies with folksonomies. International Journal of Information Management29(5), 407–415.

    Google Scholar

    Echarte F., Astrain J., Crdoba J. & Villadangos J.2009. Improving folksonomies quality by syntactic tag variations grouping. In Proceedings of the 2009 ACM Symposium on Applied Computing, 1226–1230. http://dl.acm.org/citation.cfm?id=1529559&dl=ACM&coll=DL&CFID=179648186&CFTOKEN=60450037.

    Google Scholar

    Farhan H. R. & Sanderson M.2008. Measuring the quality of an E-Government folksonomy. http://www.seg.rmit.edu.au/mark/publications/my_papers/E-government_Folksonomy.pdf.

    Google Scholar

    Floeck F., Putzke J., Steinfels S., Fischbach K. & Schoder D.2011. Imitation and quality of tags in social bookmarking systems-collective intelligence leading to folksonomies. In On Collective Intelligence: Advances in Intelligent and Soft Computing, Bastiaens, T. J., Baumöl, U. & Krämer, B. J. (eds). Springer Berlin Heidelberg, 76, 75–91. http://link.springer.com/chapter/10.1007/978-3-642-14481-3_7.

    Google Scholar

    Folksonomy Management2014. Folksonomy Management. http://www.if4it.com/SYNTHESIZED/DISCIPLINES/Folksonomy_Management_Home_Page.html#INTRODUCTION.

    Google Scholar

    Franz B. & Richardson J.2007. http://search.cpan.org/snowhare/Lingua-Stem-0.82/lib/Lingua/Stem.pod.

    Google Scholar

    Ga D., Zouaq A., Torniai C., Jovanovi J. & Hatala M.2011. An approach to folksonomy-based ontology maintenance for learning environments. IEEE Transactions on Learning Technologies4(4), 301–314.

    Google Scholar

    Geldart J. & Cummins S.2010. The automatic integration of folksonomies with taxonomies using non-axiomatic logic. In Proceedings of Information System Development, 365–372. Springer Science+Business Media.

    Google Scholar

    Gemmell J., Schimoler T., Ramezani M. & Mobasher B.2009. Adapting K-nearest neighbor for tag recommendation in folksonomies. In Proceedings of the 7th Worshop on Intelligent Techniques for Web Personalization and 21th International Joint Conference on Recommender Systems in Conjunction, Artificial Intelligence, Pasadena, California, USA, 51–62.

    Google Scholar

    Gemmell J. & Shepitsen A.2008. Personalization in folksonomies based on tag clustering. In Proceedings of the 6th Workshop on Intelligent Techniques for Web Personalization and Recommender Systems, 37–48. http://www.aaai.org/Papers/Workshops/2008/WS-08-06/WS08-06-005.pdf.

    Google Scholar

    Gendarmi D., Lanubile F., Informatica D. & Orabona V. E.2006. Community-driven ontology evolution based on folksonomies. In OTM Workshops 2006, LNCS 4277, 181–188. Springer-Verlag Berlin Heidelberg.

    Google Scholar

    GNU Aspell2011. GNU Aspell. http://aspell.sourceforge.net/.

    Google Scholar

    Golder S. & Huberman B.2006. Usage patterns of collaborative tagging systems. Journal of Information Science32(2), 198–208.

    Google Scholar

    Golov E., Weller K. & Peters I.2008. TagCare: a personal portable tag repository. In International Semantic Web Conference, 2–3. http://www.phil.hhu.de/fileadmin/Redaktion/Institute/Informationswissenschaft/1227004317iswc2008_t.pdf.

    Google Scholar

    Gupta M., Li R., Yin Z. & Han J.2010. Survey on social tagging techniques. SIGKDD Explorations12(1), 58–72.

    Google Scholar

    Guy M. & Tonkin E.2006. Folksonomies tidying up tags. D-Lib Magazine, 12(1), Janauary 2006.

    Google Scholar

    Harvey M., Baillie M., Ruthven I. & Elsweiler D.2009. Folksonomic tag clouds as an aid to content indexing. CoRR abs/0911.4178. http://arxiv.org/ftp/arxiv/papers/0911/0911.4178.pdf.

    Google Scholar

    Helic D., Krner C. & Granitzer M.2012. Navigational efficiency of broad vs. narrow folksonomies. In Proceedings of the 23rd ACM Conference on Hypertext and Social Media, 63–72. ACM. http://dl.acm.org/citation.cfm?id=2310008.

    Google Scholar

    Helic D., Lerman K., Rey M., Strohmaier M. & Trattner C.2011. Pragmatic evaluation of folksonomies. In Proceedings of the 20th International Conference on World Wide Web, 417–426. ACM.

    Google Scholar

    Hepp M., Bachlechner D. & Siorpaes K.2006. OntoWiki: community-driven ontology engineering and ontology usage based on Wikis. In Proceedings of the 2006 International Symposium on Wikis, 143–144. http://dl.acm.org/citation.cfm?id=1149487.

    Google Scholar

    Herwig J.2008. Folksonomy the semantic puzzle. http://blog.semantic-web.at/tag/folksonomy/.

    Google Scholar

    Hong L., Chi E. & Budiu R.2008. SparTag.us: a low cost tagging system for foraging of web content. In Proceedings of the Working Conference on Advanced Visual Interfaces (AVI08), 65–72. ACM. http://dl.acm.org/citation.cfm?id=1385582.

    Google Scholar

    Hotho A., Jschke R., Schmitz C. & Stumme G.2006. FolkRank: a ranking algorithm for folksonomies. In FGIR, 2–5. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.94.5271&rep=rep1&type=pdf .

    Google Scholar

    Hsueh P., Melville P. & Sindhwani V.2009. Data quality from crowdsourcing: a study of annotation selection criteria. In Proceedings of the NAACL HLT 2009 Workshop on Active Learning for Natural Language Processing, 27–35. http://dl.acm.org/citation.cfm?id=1564137.

    Google Scholar

    Jeong J. W., Hong H. K. & Lee D. H.2011. i-TagRanker: an efficient tag ranking system for image sharing and retrieval using the semantic relationships between tags. Multimedia Tools and Applications62(2), 451–478.

    Google Scholar

    Jin S., Lin H. & Su S.2009. Query expansion based on folksonomy tag co-occurrence analysis. In Proceedings of IEEE International Conference on Granular Computing (GRC 09), 300–305.

    Google Scholar

    jSongMiner2014. jSongMiner. http://jmir.sourceforge.net/jSongMiner.html.

    Google Scholar

    Kang J. & Lerman K.2011. Leveraging user diversity to harvest knowledge on the social web. Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE 3rd International Conference on Social Computing (SocialCom), 215–222. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6113117.

    Google Scholar

    Kawase R. & Herder E.2011. Classification of user interest patterns using a virtual folksonomy. In Proceeding of the 11th Annual International ACM/IEEE Joint Conference on Digital libraries (JCDL 11), 105–108. http://portal.acm.org/citation.cfm?doid=1998076.1998095.

    Google Scholar

    Kiu C. & Tsui E.2008. TaxoFolk: a hybrid taxonomy—folksonomy classification for enhanced knowledge navigation. Knowledge Management Research & Practice8(1), 24–32.

    Google Scholar

    Knerr T.2001. Tagging ontology towards a common ontology for folksonomies, 3–8. http://tagont.googlecode.com/files/TagOntPaper.pdf.

    Google Scholar

    Körner C., Kern R. & Strohmaier M.2010. Of categorizers and describers: an evaluation of quantitative measures for tagging motivation. In 21st ACM SIGWEB Conference on Hypertext and Hypermedia (HT2010), 157–166. ACM.

    Google Scholar

    Krestel R. & Chen L.2008. The art of tagging: measuring the quality of tags. In The Semantic Web, 3rd Asian Semantic Web Conference (ASWC 2008), LNCS 5367, 257–271. Springer-Verlag Berlin Heidelberg.

    Google Scholar

    Kwak H., Shin H., Yoon J. & Moon S.2009. Connecting users with similar interests across multiple web services. In ICWSM, 1–4. http://www.aaai.org/ocs/index.php/ICWSM/09/paper/viewPDFInterstitial/189/506.

    Google Scholar

    Laniado D., Eynard D. & Colombetti M.2007. Using WordNet to turn a folksonomy into a hierarchy of concepts. In Semantic Web Application and Perspectives—Fourth Italian Semantic Web Workshop, 192–201. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.94.4393&rep=rep1&type=pdf#page=200.

    Google Scholar

    Layne S. S.1994. Some issues in the indexing of images. Journal of the American Society for Information Science45(8), 583–588.

    Google Scholar

    Lee S., Neve W. D. & Ro Y. M.2010. Tag refinement in an image folksonomy using visual similarity and tag co-occurrence statistics. Signal Processing: Image Communication25(10), 761–773.

    Google Scholar

    Lee S., Neve W. D. & Ro Y. M.2012. Towards data-driven estimation of image tag relevance using visually similar and dissimilar folksonomy images. In Proceedings of the 2012 Workshop on Socially-Aware Multimedia (SAM 2012); held in Conjunction with ACM Multimedia 2012, 3–8. http://www.citeulike.org/user/wmdeneve/article/11007815.

    Google Scholar

    Lee S. E. & Han S. S.2007. Qtag: introducing the qualitative tagging system. In Proceedings of the 18th Conference on Hypertext and Hypermedia (HT 07), 35–36. http://dl.acm.org/citation.cfm?id=1286250&dl=ACM&coll=DL&CFID=179648186&CFTOKEN=60450037.

    Google Scholar

    Li J., Ma Q., Asano Y. & Yoshikawa M.2012. Improving folksonomy tag quality. In WAIM 2012 Workshops, LNCS 7419, 264–275. Springer-Verlag Berlin Heidelberg.

    Google Scholar

    Li X., Snoek C. G. M. & Worring M.2009. Learning social tag relevance by neighbor voting. IEEE Transactions on Multimedia11(7), 1310–1322.

    Google Scholar

    Limpens F., Gandon F. & Buffa M.2008. Bridging ontologies and folksonomies to leverage knowledge sharing on the social web: a brief survey. In 23rd IEEE/ACM International Conference on Automated Software Engineering-Workshops (ASE), 13–18. IEEE. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4686305.

    Google Scholar

    Lipczak M.2008. Tag recommendation for folksonomies oriented towards individual users. ECML PKDD Discovery Challenge84. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.183.2330&rep=rep1&type=pdf#page=92.

    Google Scholar

    Liu D., Zhang M. W., Yang Y. & Hong Jiang X. S. H.2009. Tag quality improvement for social images. In International Conference on Multimedia and Expo (ICME), 350–353. IEEE.

    Google Scholar

    Liu D. & Zhang X. H. H.2011. Content-based tag processing for Internet social images. Multimedia Tools and Applications51(2), 723–738.

    Google Scholar

    Magnuson L.2008. Folksonomies: meaning, discourse, and information retrieval, 1–15. http://www.cais-acsi.ca/proceedings/2009/Magnuson_2009.pdf.

    Google Scholar

    Markines B., Cattuto C. & Menczer F.2009. Social spam detection. In Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb09), 41. ACM Press. http://portal.acm.org/citation.cfm?doid=1531914.1531924.

    Google Scholar

    Matthes F., Neubert C. & Steinhoff A.2012. Structuring folksonomies with implicit tag relations. In Proceedings of the 23rd ACM Conference on Hypertext and Social Media, 315–316. http://dl.acm.org/citation.cfm?id=2310051&dl=ACM&coll=DL&CFID=179648186&CFTOKEN=60450037.

    Google Scholar

    Maurer B.Mcmillen C., Abraham D. & Blum M.2008. reCAPTCHA: human-based character recognition via web security measures. Science321(5895), 1465–1468.

    Google Scholar

    McCarthy L. & Conners D.2006. Folksonomies in action. http://folksonomiesinaction.blogspot.com/.

    Google Scholar

    Mejias U.2005. Tag literacy. http://blog.ulisesmejias.com/2005/04/26/tag-literacy/.

    Google Scholar

    Morrison P. J.2008. Tagging and searching: search retrieval effectiveness of folksonomies on the World Wide Web. Information Processing & Management44(4), 1562–1579.

    Google Scholar

    Muller M. J.2007. Comparing tagging vocabularies among four enterprise tag-based services. In Proceedings of the 2007 International ACM Conference on Supporting Group Work, 341–350. ACM Press. http://portal.acm.org/citation.cfm?doid=1316624.1316676.

    Google Scholar

    Nandipati A.2011. Assessment of metadata associated with geotag pictures. Masters thesis, University of Muenster.

    Google Scholar

    Nauerz A., Bakalov F., Welsch M. & Birgitta K.2009. New tagging paradigms for content recommendation in Web 2. 0 portals. In Workshop on Adaptation and Personalization for Web 2.0, 143–147.

    Google Scholar

    Noh T., Lee J., Park S., Lee S. & Kim K.2010. Tag quality feedback: a framework for quantitative and qualitative feedback on tags of social web. In PRICAI 2010, LNAI 6230, 637–642. Springer-Verlag Berlin Heidelberg.

    Google Scholar

    Noll MG & Gibbins N.2009. Telling experts from spammers: expertise ranking in folksonomies. In SIGIR09, 19–23. ACM.

    Google Scholar

    Noy N.2008. Community-based ontology development, alignment, and evaluation. http://kmi.open.ac.uk/events/sssw08/presentations/Noy-SSSW_2008_Noy.pdf.

    Google Scholar

    Pan J., Taylor S. & Thomas E.2009. Reducing ambiguity in tagging systems with folksonomy search expansion. In Proceedings of the 6th European Conference on the Semantic Web: Research and Applications, 669–683. http://link.springer.com/chapter/10.1007/978-3-642-02121-3_49.

    Google Scholar

    Papadopoulos S., Vakali A. & Kompatsiaris Y.2011. Community detection in collaborative tagging systems. Community-Built Databases, 107–131. Springer Berlin Heidelberg. http://link.springer.com/chapter/10.1007/978-3-642-19047-6_5.

    Google Scholar

    Pera M. S. & Lund W.2009. Folksonomies and similarity matching. Journal of the American Society for Information Science and Technology60(7), 1392–1406.

    Google Scholar

    Perry S.2009. Jumper 2.0. http://theology.asin.web.id/IT/tulisan-770/Jumper-2.0-Enterprise_474_theology-asin.html.

    Google Scholar

    Peters I.2009. Folksonomies: Indexing and Retrieval in Web 2.0, 1. Walter de Gruyter.

    Google Scholar

    Peters I. & Weller K.2008. Tag gardening for folksonomy enrichment and maintenance. Webology5(3), 1–18.

    Google Scholar

    Poorgholami M., Jalali M., Rehan S. & Asgari T.2013. Spam detection in social bookmarking websites. IEEE 4th International Conference on Software Engineering and Service Science, 56–59. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6615254.

    Google Scholar

    Quattrone G., Capra L., De Meo P., Ferrara E. & Ursino D.2011. Effective retrieval of resources in folksonomies using a new tag similarity measure. In Proceedings of the 20th ACM International Conference on Information and Knowledge Management, 545–550. http://arxiv.org/abs/1207.6033.

    Google Scholar

    Rásto K., Tvaroek M. & Bielikova M.2013. Web search results exploration via cluster-based views and zoom-based navigation. Journal of Universal Computer Science19(15), 2320–2346.

    Google Scholar

    Ravendran R.2012. Usability evaluation of a tag-based interface. Journal of Usability Studies7(4), 143–160.

    Google Scholar

    Rodenhausen T., Anjorin M., Garcia R. D., Rensing C., Steinmetz R. & Dominguez R.2012. Ranking resources in folksonomies by exploiting semantic information categories and subject descriptors. In Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies, 11. ACM.

    Google Scholar

    Rossi L. C. D.2006. Folksonomies: tags strengths, weaknesses and how to make them work. http://www.masternewmedia.org/news/2006/02/01/folksonomies_tags_strengths_weaknesses_and.htm.

    Google Scholar

    Saab D. J.2011. An emergent culture model for discerning tag semantics in folksonomies. In Proceedings of the 2011 iConference (iConference11), 552–560. http://portal.acm.org/citation.cfm?doid=1940761.1940837.

    Google Scholar

    Sen S.Harper F. M., Lapitz A. & Riedlet J.2007. The quest for quality tags. In Proceedings of the 2007 International ACM Conference on Supporting Group Work, 361–370. ACM. http://www.grouplens.org/system/files/group07-sen.pdf.

    Google Scholar

    Sen S., Lam S. & Rashid A.2006. Tagging, communities, vocabulary, evolution. In Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work, 181–190. ACM Press. http://portal.acm.org/citation.cfm?doid=1180875.1180904.

    Google Scholar

    Sen S., Vig J. & Riedl J.2009. Tagommenders: connecting users to items through tags. In WWW 2009 MADRID! Track: Social Networks and Web 2.0/Session: Recommender Systems, 1–10.

    Google Scholar

    Shvaiko P. & Euzenat J.2008. Ten challenges for ontology matching. In On the Move to Meaningful Internet Systems: (OTM 2008), Meersman, R., Tari, Z. & Herrero, P. (eds). Springer Berlin Heidelberg, 1164–1182.

    Google Scholar

    Sigurbjrnsson B. & van Zwol R.2008. Flickr tag recommendation based on collective knowledge. In Proceeding of the 17th International Conference on World Wide Web (WWW08), 327–336. ACM Press. http://portal.acm.org/citation.cfm?doid=1367497.1367542.

    Google Scholar

    Solskinnsbakk G., Atle J., Haderlein V., Myrseth P. & Cerrato O.2012. Quality of hierarchies in ontologies and folksonomies. Data and Knowledge Engineering74, 13–25.

    Google Scholar

    Solskinnsbakk G. & Gulla J.2011. Semantic annotation from social data. In 4th International Workshop Social Data on the Web (SDoW 2011). https://files.ifi.uzh.ch/ddis/iswc_archive/iswc/pps/web/iswc2011.semanticweb.org/fileadmin/iswc/Papers/Workshops/SDoW/sdow2011_paper_3.pdf.

    Google Scholar

    Solskinnsbakk G. & Gulla J. A.2001. Mining tag similarity in folksonomies. In Proceedings of 3rd International Workshop on Search and Mining User-Generated Contents, 53–60.

    Google Scholar

    Sood S. C., Owsley S. H., Hammond K. J. & Birnbaum L.2007. TagAssist: automatic tag suggestion for blog posts. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM 2007).

    Google Scholar

    Sordo M.Gouyon F., Sarmento L. & Celmaet O.2013. Inferring semantic facets of a music folksonomy with Wikipedia. Journal of New Music Research42(4), 346–363.

    Google Scholar

    Spiteri L.2011. Faceted navigation of social tagging applications. https://www.academia.edu/2374931/Faceted_navigation_of_social_tagging_applications.

    Google Scholar

    Spiteri L. F.2007a. Structure and form of folksonomy tags: the road to the public library catalogue. Webology4(2), article no. 41.

    Google Scholar

    Spiteri L. F.2007b. The structure and form of folksonomy tags: the road to the public library catalog. Information Technology and Libraries26(3), 13–25.

    Google Scholar

    Stock W. G.2007. Folksonomies and science communication. Information Services & Use27, 97–103.

    Google Scholar

    Strohmaier M., Christian K. & Kern R.2009. Why do users tag? Detecting users motivation for tagging in social tagging systems. In Fourth International AAAI Conference on Weblogs and Social Media, 339–342.

    Google Scholar

    Strohmaier M., Helic D., Benz D., Orner C. K. & Kern R.2012a. Evaluation of folksonomy induction algorithms. ACM Transactions on Intelligent Systems and Technology (TIST)3(4), 74.

    Google Scholar

    Strohmaier M., Körner C. & Kern R.2012b. Understanding why users tag: a survey of tagging motivation literature and results from an empirical study. Web Semantics (Online)17(C), 1–11.

    Google Scholar

    Sturtz D. N.2004. Communal categorization: the folksonomy. INFO622 Content Representation. http://davidsturtz.com/drexel/622/communal-categorization-the-folksonomy.html.

    Google Scholar

    Syn S. Y. & Spring M. B.2009. Tags as keywords comparison of the relative quality of tags and keywords. Proceedings of the American Society for Information Science and Technology46(1), 1–19.

    Google Scholar

    Szomszor M., Alani H., Cantador I., Hara K. O. & Shadbolt N.2008. Semantic modelling of user interests based on cross-folksonomy analysis. In ISWC 2008, LNCS 5318, 632–648. Springer-Verlag Berlin Heidelberg.

    Google Scholar

    Tang R., Zuo J., Xu K., Zheng J. & Wang Y.2010. An intelligent semantic-based tag cleaner for folksonomies. In 2010 International Conference on Intelligent Computing and Integrated Systems (ICISS), 773–776. IEEE.

    Google Scholar

    Taylor A.2004. The Organization of Information, 2nd edition. Libraries Unlimited.

    Google Scholar

    Trant J.2006. Social classification and folksonomy in art museums: early data from the steve.museum tagger prototype. A Paper for the ASIST-CR Social Classification Workshop, 1–27. http://www.archimuse.com/papers/asist-CR-steve-0611.pdf.

    Google Scholar

    Tudorache T., Noy N., Tu S. & Musen M.2008. Supporting collaborative ontology development in Protg. The Semantic Web-ISWC 2008, 17–32. http://link.springer.com/chapter/10.1007/978-3-540-88564-1_2.

    Google Scholar

    Vallet D., Cantador I. & Jose J. M.2010. Personalizing web search with folksonomy-based user and document profiles. In ECIR 2010, LNCS 5993, 420–431. Springer-Verlag Berlin Heidelberg.

    Google Scholar

    Vanderlei T. & Durão F.2007. A cooperative classification mechanism for search and retrieval software components. In Proceedings of the 2007 ACM Symposium on Applied Computing (SAC07), 866–871. ACM Press. http://portal.acm.org/citation.cfm?doid=1244002.1244192.

    Google Scholar

    Veres C.2006. Concept modeling by the masses: folksonomy structure and interoperability. In Conceptual Modeling - ER 2006, LNCS 4215, 325–338. Springer-Verlag Berlin Heidelberg.

    Google Scholar

    Waltl B.2012. Partitioning instead of clustering: an alternative approach for mining structured content in folksonomies. http://www.matthes.informatik.tu-muenchen.de/file/b14ej8z7mffa/sebis-Public-Website/-/Guided-Research-Bernhard-Waltl/Guided-Research-Bernhard-Waltl.pdf.

    Google Scholar

    Wang J., Hua X. S. & Li S.2009. Tag refinement by regularized LDA. In Proceedings of the 17th ACM International Conference on Multimedia, 573–576. http://dl.acm.org/citation.cfm?id=1631359.

    Google Scholar

    Wang M., Ni B., Hua X. S. & Chua T. S.2012. Assistive tagging. ACM Computing Surveys44(4), 1–24.

    Google Scholar

    Warden P.2007. Can you automatically generate good tags. http://petewarden.com/2007/12/03/can-you-automat/.

    Google Scholar

    Wei X.Peng F. & Dumoulin B.2008. Analyzing web text association to disambiguate abbreviation in queries. In Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 751–752. ACM. http://dl.acm.org/citation.cfm?doid=1390334.1390485.

    Google Scholar

    Wetzker R. & Bauckhage C.2010. I tag, you tag: translating tags for advanced user models. In Proceedings of the 3rd ACM International Conference on Web Search and Data Mining, 71–80. ACM.

    Google Scholar

    Whatever S. A.2009. Knowledge plaza. http://theology.asin.web.id/IT/tulisan-770/Knowledge-Plaza_2639_theology-asin.html .

    Google Scholar

    WordNet2010. WordNet. http://wordnet.princeton.edu/.

    Google Scholar

    Xia Z., Peng J., Feng X. & Fan J.2013. Automatic abstract tag detection for social image tag refinement and enrichment. Journal of Signal Processing Systems74(1), 5–18.

    Google Scholar

    Xu G., Zong Y., Jin P., Pan R. & Wu Z.2013. KIPTC: a kernel information propagation tag clustering algorithm. Journal of Intelligent Information Systems45(1), 1–18. http://link.springer.com/10.1007/s10844-013-0262-7.

    Google Scholar

    Yang H. & Lee C.2011. Identifying spam tags by mining tag semantics. In 3rd International Conference on Data Mining and Intelligent Information Technology Applications (ICMiA), 263–268. http://ir.nuk.edu.tw:8080/ir/bitstream/310360000Q/11836/2/icmia2011.pdf.

    Google Scholar

    Yazdani S.Ivanow I., Analoui M., Berangi R. & Ebrahimi T.2012. Spam fighting in social tagging systems. In Sociinfo 2012, LNCS 7710, 448–461. Springer-Verlag Berlin Heidelberg.

    Google Scholar

    Yoo D., Choi K., Suh Y. & Kim G.2013. Building and evaluating a collaboratively built structured folksonomy. Journal of Information Science39(5), 593–607.

    Google Scholar

    Yoo D. & Suh Y.2010. User-categorized tags to build a structured folksonomy. In Second International Conference on Communication Software and Networks (ICCSN10), 160–164. IEEE.

    Google Scholar

    Zanardi V. & Capra L.2008. Social ranking: uncovering relevant content using tag-based recommender systems. In Proceedings of the 2008 ACM Conference on Recommender Systems, 51–58. ACM. http://dl.acm.org/citation.cfm?id=1454018.

    Google Scholar

    Zhang L., Tang J. & Zhang M.2012. Integrating temporal usage pattern into personalized tag prediction. In Web Technologies and Applications, Sheng, Q. Z., Wang, G., Jensen, C. S. & Xu, G. (eds). LNCS 7235, 354–365.Springer-Verlag Berlin Heidelberg.

    Google Scholar

    Zhdanova A. & Shvaiko P.2006. Community-driven ontology matching. In The Semantic Web: Research and Applications, Sure, Y. & Domingue, J. (eds). LNCS 4011, 34–49. Springer Berlin Heidelberg. http://link.springer.com/chapter/10.1007/11762256_6.

    Google Scholar

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    Fouzia Jabeen, Shah Khusro. 2015. Quality-protected folksonomy maintenance approaches: a brief survey. The Knowledge Engineering Review 30(5)521−544, doi: 10.1017/S0269888915000120
    Fouzia Jabeen, Shah Khusro. 2015. Quality-protected folksonomy maintenance approaches: a brief survey. The Knowledge Engineering Review 30(5)521−544, doi: 10.1017/S0269888915000120
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RESEARCH ARTICLE   Open Access    

Quality-protected folksonomy maintenance approaches: a brief survey

  • Department of Computer Science

  • Published online: 30 October 2015
The Knowledge Engineering Review  30,  2015, 30(5): 521−544  |  Cite this article

Abstract: Abstract: Folksonomy gives liberty to its users to freely assign chosen keywords as tags, and this is the main reason behind its popularity. Apart from freedom, this system also reflects the collective intelligence of the crowd. However, this freedom and liberty can degrade quality of the folksonomy. It is required that quality of the folksonomy must remain consistently excellent and does not degrade with the passage of time. This is a survey paper, in which we present a brief survey of the research efforts intended to maintain a quality-protected folksonomy. We have organized our paper by looking at the problem from four aspects namely selection of quality tags, tag management features provided by folksonomy applications, folksonomy cleaning and interoperability of tags across platforms. We conclude our review with some of the interesting research topics, which need to be explored further. Our conclusion will be relevant and beneficial for engineers and designers who aim to design and maintain a quality-protected folksonomy.

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    • This research is undertaken by the first author for partial fulfilment of PhD degree requirements with support of Higher Education Commission of Pakistan (HEC).

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    Cite this article
    Fouzia Jabeen, Shah Khusro. 2015. Quality-protected folksonomy maintenance approaches: a brief survey. The Knowledge Engineering Review 30(5)521−544, doi: 10.1017/S0269888915000120
    Fouzia Jabeen, Shah Khusro. 2015. Quality-protected folksonomy maintenance approaches: a brief survey. The Knowledge Engineering Review 30(5)521−544, doi: 10.1017/S0269888915000120
    shu

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