El-Hachem, Jinan, Shaban-Nejad, Arash, Haarslev, Volker, DubŽ, Laurette and Buckeridge, David L. (2012) An OWL 2-Based Knowledge Platform Combining the Social and Semantic Webs for an Ambient Childhood Obesity Prevention System. Procedia Computer Science, 10 . pp. 110-119. ISSN 18770509
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Official URL: http://dx.doi.org/10.1016/j.procs.2012.06.018
Abstract
Amid the extremely active Semantic Web community and the Social Web's exceptionally rising popularity, experts believe that an amplified fusion between the two webs will give rise to the next huge advancement in Web intelligence. Such advances can particularly be translated into ambient and ubiquitous systems and applications. In this paper, we delve into the recent advances in knowledge representation, semantic web, natural language processing and online social networking data and concepts, to propose an inclusive platform and framework defining ambient recommender and decision support systems that aim at facilitating cross-sectional analysis of the domain of childhood obesity and generating both generic and customized preventive recommendations.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering |
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Item Type: | Article |
Refereed: | Yes |
Authors: | El-Hachem, Jinan and Shaban-Nejad, Arash and Haarslev, Volker and DubŽ, Laurette and Buckeridge, David L. |
Journal or Publication: | Procedia Computer Science |
Date: | 2012 |
Digital Object Identifier (DOI): | 10.1016/j.procs.2012.06.018 |
Keywords: | Ambient systems; Web Ontology Language (OWL); Social Web; Semantic Web; Recommender Systems; Biomedical Ontologies; Natural Language Processing; Childhood Obesity Prevention |
ID Code: | 976806 |
Deposited By: | Danielle Dennie |
Deposited On: | 28 Jan 2013 13:53 |
Last Modified: | 18 Jan 2018 17:43 |
References:
[1] Ducatel K, Bogdanowicz M, Scapolo F, Leijten J, Burgelman JC. Scenarios for ambient intelligence in 2010, (ISTAG’01 Final Report). Seville: IPTS; 2001.[2] Dubé L, Bechara A, Böckenholt U, Ansari A, Dagher A. et al. Towards a brain-to-society systems model of individual choice. Market Lett, 2008; 19:323-336.
[3] Singh GK. Changes in state-specific childhood obesity and overweight prevalence in the United States from 2003 to 2007. Arch Pediatr Adolesc Med. 2010; 164(7):598-607.
[4] Dubé L. On the Brain-to-Society Model of Motivated Choice and the Whole-of-Society Approach to Obesity Prevention. In: Dubé L, Bechara A, et al., eds. Obesity prevention: the role of brain and society on individual behavior, Elsevier, 2010.
[5] Shaban-Nejad A., Buckeridge DL, Dubé L. COPE: Childhood Obesity Prevention [Knowledge] Enterprise. in Proc. of AIME 2011, LNCS 6747 Springer, 201; pp. 225-229.
[6] Cuenca Grau B, Horrocks I, Motik B., Parsia B.,Patel-Schneider P., Sattler U. OWL 2: The next step for OWL, J of Web Semantic. 2008;6(4): 309-322.
[7] Borys JM, Le Bodo Y, Jebb SA, Seidell JC, Summerbell C, et al. EPODE approach for childhood obesity prevention: methods, progress and international development. Obes Rev. 2011.
[8] Cefkin M, Glissman SM., Haas PJ, Jalali L, Maglio PP, Selinger P, Tan W. SPLASH: A Progress Report on Building a Platform for a 360 Degree View of Health. In Proc. of the 5th INFORMS DM-HI Workshop, 2010.
[9] Mika P. Current issues with Social Network Representations, Yahoo! Research, Nov. 22, 2008.
[10] Mika P. Social Networks and the Semantic Web. Sem. Web and Beyond: Computing for Human Experience, Springer, 2007.
[11] Gruber T R. Collective Knowledge Systems: Where the Social Web meets the Semantic Web, J. of Web Semantics, 2008; 6(1).
[12] Baader F. et al. The Description Logic Handbook: Theory, Implementation and Applications, Cambridge U. Press; 2006.
[13] Bizer C, Cyganiak R, Heath T, “How to Publish Linked Data on the Web”; 2007.
[14] San Martin M, Gutierrez C. Representing, Querying and Transforming Social Networks with RDF/SPARQL, The Semantic Web: Research and Applications, Springer, Berlin/Heidelberg, 2009; pp. 293-307.
[15] Object Management Group OMG, “MOF Support for Semantic Structures (SMOF) Revised Joint Submission”, OMG Document formal/2010-08-06, http://www.omg.org/spec/SMOF/1.0/Source/10-08-06.pdf, 2010.
[16] OWL 2 Web Ontology Language Overview, http://www.w3.org/TR/owl2-overview/, W3C Recommendation; 27 Oct 2009.
[17] Cunningham H. GATE, a General Architecture for Text Engineering, J of Computers and the Humanities. 2002; 223-254.
[18] The KIM Platform, URL: http://www.ontotext.com/kim/.
[19] El-Hachem J, Haarslev V. A User and NLP-Assisted Strategic Workflow for a Social Semantic OWL 2-Based Knowledge Platform. In: Semantic Analysis in Social Media, EACL 2012, April 2012.
[20] Lien L, Lien N, Heyerdahl S, Thoresen M, Bjertness E Consumption of soft drinks and hyperactivity, mental distress, and conduct problems among adolescents in Oslo, Norway. Am J Public Health. 2006; pp.1815-1820.
[21] Horrocks I, Kutz O, Sattler U. The even more irresistible SROIQ, In Proceedings of the 10th International Conference on Principles of Knowledge Representation and Reasoning (KR 2006), pp.57-67. AAAI Press, Menlo Park; 2006.
[22] Goldberg, D. Nichols, D., Oki, B.M., Terry, D. Using collaborative filtering to weave an information tapestry. Commun. ACM. 1992;35(12): 61-70.
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