research-article

Using social data as context for making recommendations: an ontology based approach

Authors:

Salma Noor,

Kirk MartinezAuthors Info & Claims

CIAO '09: Proceedings of the 1st Workshop on Context, Information and Ontologies

Article No.: 7, Pages 1 - 8

https://doi.org/10.1145/1552262.1552269

Published: 01 June 2009 Publication History

Get Access

Abstract

Web-based knowledge systems support an impressive and growing amount of information. Among the difficulties faced by these systems is the problem of overwhelming the user with a vast amount of data, often referred to as information overload. The problem has escalated with the ever increasing issues of time constraints and the extensive use of handheld devices. The use of context is one possible way out helping with this situation. To provide a more robust approach to context gathering we propose the use of Social Web technologies alongside the Semantic Web. As the social web is heavily used it could provide a better understanding of a user's interests and intentions. The proposed system gathers information about users from their social web identities and enriches it with ontological knowledge. Thus an interest model for the user can be created which can serve as a good source of contextual knowledge. This work bridges the gap between the user and system searches by analyzing the virtual existence of a user and making interesting recommendations accordingly.

References

[1]

Marlow, C., Naaman, M., Boyd, D., Davis, M. 2006. HT06, Tagging paper, Taxonomy, Flickr, Academic Article, ToRead. In Proceedings of International Conference on Hypertext (Odense, Denmark 2006)

Digital Library

Google Scholar

[2]

Li, X., Guo, L., Zhao, Y. E. 2008. Tag-based Social Interest Discovery. In the Proceedings of 19th International World Wide Web Conf. (WWW), (Beijing, China 2008)

Digital Library

Google Scholar

[3]

Gruber, T. 2008. Collective Knowledge Systems: Where the Social Web meets the Semantic Web. Journal of Web Semantics 6(1) (2008)

Digital Library

Google Scholar

[4]

Mathes, A. 2004. Folksonomies - Cooperative Classification and Communication Through Shared Metadata. Computer Mediated Communication - LIS590CMC (December 2004)

Google Scholar

[5]

Szomszor, M., Cantador, I., Alani, H. 2008. Correlating User Profiles from Multiple Folksonomies. In the Proceedings of International Conference on Hypertext (HT 2008), (Pittsburgh, PA, USA, 2008)

Digital Library

Google Scholar

[6]

Miller, G. A. 1995. WordNet: A Lexical Database for English. Communications of the Association for Computing Machinery, 38(11), pp. 39--41.

Digital Library

Google Scholar

[7]

Bojars, U., Breslin, J. G., Finn, A., Decker, S. 2008. Using the Semantic Web for Linking and Reusing Data Across Web2.0 Communities. Web Semantics: Science, Services and Agents on the World Wide Web 6(1), 21--28 (2008)

Digital Library

Google Scholar

[8]

Specia, L., Motta, E. 2007. Integrating Folksonomies With the Semantic Web. In ESWC 2007. LNCS, vol. 4519. Springer, Heidelberg (2007)

Digital Library

Google Scholar

[9]

Kim, H., Yang, S., Song, S., Breslin, J. G., Kim, H. Tag Mediated Society with SCOT Ontology. International Semantic Web Conference (ISWC). (2007).

Google Scholar

[10]

Suchanek, F. M., G. Kasneci & G. Weikum. 2007. YAGO: A Core of Semantic knowledge. In the Proceedings of World Wide Web Conference (WWW) (2007).

Digital Library

Google Scholar

[11]

Brickley, D., Miller, L. 2005. FOAF Vocabulary Specification, working draft, 2005. DOI=http://xmlns.com/foaf/0.1.

Google Scholar

[12]

Miles, A., Brickley, D., ed. 2004. SKOS Mapping Vocabulary Specification. W3C. DOI=http://www.w3.org/2004/02/skos/mapping/spec/2004-11-11.html.

Google Scholar

[13]

Szomszor, M., Alani, H., Cantador, I., O'Hara, K., Shadbolt, N. 2008. Semantic Modelling of User Interests based on Cross-Folksonomy Analysis. In ISWC 7th International Semantic Web Conference (Karlsruhe, Germany, October 26--30, 2008).

Digital Library

Google Scholar

[14]

Cantador, I., Szomszor, M., Alani, H., Fernández, M., Castells, P. 2008. Enriching Ontological User Profiles with Tagging History for Multi-Domain Recommendations. In CISWeb 1st International Workshop on Collective Semantics: Collective Intelligence & the Semantic Web, (Tenerife, Spain, June, 2008).

Google Scholar

[15]

Passant, A., Laublet, P., 2008. Meaning Of A Tag: A Collaborative Approach to Bridge the Gap Between Tagging and Linked Data. In Proceedings of the World Wide Web Conference WWW 2008 Workshop Linked Data on the Web (LDOW2008), (Beijing, China, Apr 2008).

Google Scholar

[16]

Iturrioz, J., Diaz, O., Arellano, C.,. 2007. Towards Federated Web2.0 Sites: The Tagmas Approach. In Tagging and Metadata for Social Information Organization Workshop, World Wide Web Conference (WWW), 2007.

Google Scholar

[17]

Golder, S. A., Huberman, B. A. 2006. Usage Patterns of Collaborative Tagging Systems. Journal of Information Science 32, 198--208 (2006)

Digital Library

Google Scholar

[18]

Vallet, D., Castells, P., Fernández, M., Mylonas, P., Avrithis, Y. (2007). Personalised Content Retrieval in Context Using Ontological Knowledge. IEEE Transactions on Circuits and Systems for Video Technology, 17 (3), pp. 336--346.

Digital Library

Google Scholar

[19]

Sinclair, P., Lewis, P. and Martinez, K. (2007) Dynamic Link Service 2.0: using Wikipedia as a linkbase. In the Proceedings of Hypertext Conference 2007, (Manchester, United Kingdom, 10--12 September 2007)

Digital Library

Google Scholar

[20]

Crofts, N., Doerr, M., Gill, T., Stead, S., Matthew (2006), Definition of the CIDOC Conceptual Reference Model, (October 2006). DOI=http://cidoc.ics.forth.gr/docs/cidoc_crm_version_4.2.1.pdf

Google Scholar

[21]

Addis, M. J., Hafeez, S., Prideaux, D., Lowe, R., Lewis, P. H., Martinez, K. and Sinclair, P. A. S. (2006) The eCHASE System for Cross-border Use of European Multimedia Cultural Heritage Content in Education and Publishing. In the Proceedings of AXMEDIS 2006: 2nd International Conference on Automated Production of Cross Media Content for Multi-channel Distribution, ICSRiM --(Leeds, UK, 12--15 December 2006)

Google Scholar

[22]

Kim H., Chan P. (2003)., Learning Implicit User Interest Hierarchy for Context in Personalization. In Proceedings of the 2003 International Conference on Intelligent User Interfaces (Miami, Florida, 2003).

Digital Library

Google Scholar

[23]

Bobillo, F., Delgado, M., G_omez-Romero, J.: Representation of context-dependant Knowledge in Ontologies: A model and An Application. Expert Systems with Applications, 35, 1899--1908 (2008)

Digital Library

Google Scholar

[24]

Kauppinen, T., Henriksson, R., Sinkkil, R., Lindroos, R., Vainen, J., Hyvonen, E.: Ontology-based Disambiguation of Spatiotemporal Locations. In the Proceedings of 1st International Workshop on Identity and Reference on the Semantic Web (IRSW2008), 5th European Semantic Web Conference (ESWC 2008), (Tenerife, Spain, June 1--5 2008).

Google Scholar

[25]

Auer, S., Bizer, C., Kobilarov, G., Lehmann, J.,. 2007. Dbpedia: A Nucleus for a Web of Open Data. In the Proceedings of 6th International Semantic Web Conference (ISWC, 2007).

Digital Library

Google Scholar

[26]

Google. Social Graph API's "otherme" method. Google code Labs, DOI=http://code.google.com/apis/socialgraph/docs/otherme.html.

Google Scholar

[27]

Angeletou, S., Sabou, M., Motta, E.,. 2008. Semantically Enriching Folksonomies with FLOR. In the Proceedings of the 5th Europian Semantic Web Conference. (ESWC). Workshop: Collective Intelligence & the Semantic Web, (Tenerife, Spain, 2008).

Google Scholar

Cited By

View all

Kornyshova EGressier-Soudan E(2023)Conceptual Model of User Experience for PersonalizationInformation Systems10.1007/978-3-031-30694-5_29(397-406)Online publication date: 20-Apr-2023
https://doi.org/10.1007/978-3-031-30694-5_29
Sejwal VAbulaish M(2020)CAMO: A context-aware movie ontology generated from LOD and movie databasesMultimedia Tools and Applications10.1007/s11042-020-10076-4Online publication date: 27-Oct-2020
https://doi.org/10.1007/s11042-020-10076-4
Buccafurri FLax GNocera AUrsino D(2019)A system for extracting structural information from Social Network accountsSoftware—Practice & Experience10.1002/spe.228045:9(1251-1275)Online publication date: 4-Jan-2019
https://dl.acm.org/doi/10.1002/spe.2280
Show More Cited By

Index Terms

Recommendations

User-Oriented Context Suggestion
UMAP '16: Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization

Recommender systems have been used in many domains to assist users' decision making by providing item recommendations and thereby reducing information overload. Context-aware recommender systems go further, incorporating the variability of users' ...
Context suggestion: empirical evaluations vs user studies
WI '17: Proceedings of the International Conference on Web Intelligence

Recommender System has been successfully applied to assist user's decision making by providing a list of recommended items. Context-aware recommender system additionally incorporates contexts (such as time and location) into the system to improve the ...
Ontology-Based Personalised and Context-Aware Recommendations of News Items
WI-IAT '08: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01

News@hand is a news recommender system that makes use of semantic technologies to provide several on-line news recommendation services. News contents and user preferences are described in terms of concepts appearing in a set of domain ontologies. Based ...

Reviews

Reviewer: Varadraj Prabhu Gurupur

Capturing social data using Web-based systems has become easier with the advent of semantic Web technology and social Web sites such as Orkut, Facebook, MySpace, and YouTube. The interesting aspect of a social Web site is that it lures the individual user to provide information on his or her habits, friends, way of life, and many other social activities. The semantic Web technology, on the other hand, provides a useful tool to capture and store the published social information. This is a wonderful combination that will bring about a paradigm shift in gathering social information. This paper describes a process of gathering social data by using an ontology-based approach that involves the use of semantic Web technology. Noor and Martinez insightfully discuss various upcoming technologies and tools that use the semantic Web to gather and retrieve required information from Web-based systems. The approach depends heavily on the use of tags to delineate the capture of the social data. The main architecture to capture the social data described in this paper seems quite reasonable. The authors use understandable figures to describe their ideas and concepts. They also describe methods of gathering domain-specific social data. Overall, this is a very good and well-written paper. It provides a novel idea for gathering social data, using the semantic Web. Although the main concept described in this paper looks quite achievable, the scientific community might require a solid implementation to fully accept the paper's main architecture for gathering social data. When using tools such as WordNet, DBpedia, and YAGO to gather social data, the biggest challenge is synchronizing and coalescing these tools, to achieve the desired result. Online Computing Reviews Service

Access critical reviews of Computing literature here

Become a reviewer for Computing Reviews.

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

CIAO '09: Proceedings of the 1st Workshop on Context, Information and Ontologies

June 2009

79 pages

ISBN:9781605585284

DOI:10.1145/1552262

Editors:
Jose Manuel Gomez-Perez
Universidad Politecnica de Madrid
,
Peter Haase
Karlsruhe Institute of Technology
,
Marcel Tilly
European Microsoft Innovation Center
,
Paul Warren
BT Innovate

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 2009

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

CIAO '09

CIAO '09: 1st Workshop on Context, Information And Ontologies

June 1, 2009

Heraklion, Greece

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
744
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)0

Reflects downloads up to 19 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Kornyshova EGressier-Soudan E(2023)Conceptual Model of User Experience for PersonalizationInformation Systems10.1007/978-3-031-30694-5_29(397-406)Online publication date: 20-Apr-2023
https://doi.org/10.1007/978-3-031-30694-5_29
Sejwal VAbulaish M(2020)CAMO: A context-aware movie ontology generated from LOD and movie databasesMultimedia Tools and Applications10.1007/s11042-020-10076-4Online publication date: 27-Oct-2020
https://doi.org/10.1007/s11042-020-10076-4
Buccafurri FLax GNocera AUrsino D(2019)A system for extracting structural information from Social Network accountsSoftware—Practice & Experience10.1002/spe.228045:9(1251-1275)Online publication date: 4-Jan-2019
https://dl.acm.org/doi/10.1002/spe.2280
Nocera AUrsino D(2018)A new ego network model and an approach to extracting an ego network compliant with this model from a social internetworking systemInternational Journal of Web Based Communities10.1504/IJWBC.2013.0572219:4(483-518)Online publication date: 21-Dec-2018
https://dl.acm.org/doi/10.1504/IJWBC.2013.057221
Konstantakis MMichalakis KAliprantis JKalatha EMoraitou ECaridakis G(2018)A methodology for optimised cultural user personas experience - CURE architectureProceedings of the 32nd International BCS Human Computer Interaction Conference10.14236/ewic/HCI2018.10(1-8)Online publication date: 4-Jul-2018
https://dl.acm.org/doi/10.14236/ewic/HCI2018.10
Konstantakis MAliprantis JTeneketzis ACaridakis GJohn KGrammati PStefanos GChristos D(2018)Understanding user experience aspects in cultural heritage interactionProceedings of the 22nd Pan-Hellenic Conference on Informatics10.1145/3291533.3291580(267-271)Online publication date: 29-Nov-2018
https://dl.acm.org/doi/10.1145/3291533.3291580
Núñez-Valdez ELovelle JHernández GFuente ALabra-Gayo J(2018)Creating recommendations on electronic booksComputers in Human Behavior10.1016/j.chb.2014.10.05751:PB(1320-1330)Online publication date: 23-Dec-2018
https://dl.acm.org/doi/10.1016/j.chb.2014.10.057
Núñez-Valdéz ECueva Lovelle JSanjuán Martínez OGarcía-Díaz VOrdoñez de Pablos PMontenegro Marín C(2018)Implicit feedback techniques on recommender systems applied to electronic booksComputers in Human Behavior10.1016/j.chb.2012.02.00128:4(1186-1193)Online publication date: 23-Dec-2018
https://dl.acm.org/doi/10.1016/j.chb.2012.02.001
Noor SJamil SGohar NShah L(2018)Knowledge retrieval of historic concepts using semantic webCluster Computing10.1007/s10586-018-1883-yOnline publication date: 22-Feb-2018
https://doi.org/10.1007/s10586-018-1883-y
Antoniou A(2017)Social network profiling for cultural heritage: combining data from direct and indirect approachesSocial Network Analysis and Mining10.1007/s13278-017-0458-x7:1Online publication date: 23-Aug-2017
https://doi.org/10.1007/s13278-017-0458-x
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

User-Oriented Context Suggestion

Context suggestion: empirical evaluations vs user studies

Ontology-Based Personalised and Context-Aware Recommendations of News Items

Reviews

Access critical reviews of Computing literature here