Nothing Special   »   [go: up one dir, main page]

Skip to main content

Advertisement

Log in

Semantic manipulation of user’s queries and modeling the health and nutrition preferences

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

People depend on popular search engines to look for the desired health and nutrition information. Many search engines cannot semantically interpret, enrich the user’s natural language queries easily and hence do not retrieve the personalized information that fits the user’s needs. One reason for retrieving irrelevant information is the fact that people have different preferences where each one likes and dislikes certain types of food. In addition, some people have specific health conditions that restrict their food choices and encourage them to take other foods. Moreover, the cultures, where people live in, influence food choices while the search engines are not aware of these cultural habits. Therefore, it will be helpful to develop a system that semantically manipulates user’s queries and models the user’s preferences to retrieve personalized health and food information. In this paper, we harness semantic Web technology to capture user’s preferences, construct a nutritional and health-oriented user’s profile, model the user’s preferences and use them to organize the related knowledge so that users can retrieve personalized health and food information. We present an approach that uses the personalization techniques based on integrated domain ontologies, pre-constructed by domain experts, to retrieve relevant food and health information that is consistent with people’s needs. We implemented the system, and the empirical results show high precision and recall with a superior user’s satisfaction.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Notes

  1. http://www.jboss.org/.

  2. http://www.tomcat.apache.org/.

  3. https://www.w3.org/standards/techs/owl.

  4. https://www.eclipse.org.

  5. https://www.netbeans.org/.

  6. http://www.jena.apache.org/.

  7. https://www.topquadrant.com/tools/ide-topbraid-composer-maestro-edition/.

  8. https://www.confluence.ontotext.com/display/OWLIMv43/OWLIM-Lite+Reasoner.

  9. https://www.rdf4j.org/.

  10. https://www.jade.tilab.com/.

  11. https://www.ups.savba.sk/~misos/AgentOWL/doc/.

  12. https://www.wordnet.princeton.edu.

  13. http://en.wikipedia.org/wiki/Cohen's_kappa.

References

  • Dominguez D et al (2006) PIPS: an integrated environment for health care delivery and healthy lifestyle support. In: 4th Workshop on Agent applied in Healthcare, ECAI2006. http://www.csc.liv.ac.uk/~floriana/papers/ecai06.pdf. Accessed 22 June 2012

  • Al-Nazer A, Helmy T (2013) Semantic query-manipulation and personalized retrieval of health, food and nutrition information. Elsevier Open Access Procedia Comput Sci J 19:163–170

    Article  Google Scholar 

  • Barnes J, Chu D (2010) Agent-based modeling, Springer London. http://link.springer.com/10.1007/978-3-642-24004-1. Accessed 22 Mar 2014

  • Bhattacharyya P, Garg A, Felix W (2015) Analysis of user keyword similarity in online social networks. J Soc Netw Anal Min 1(3):143–158 (July 2011)

    Article  Google Scholar 

  • Ehsan N, Diane J (2015) CRAFFT: an activity prediction model based on Bayesian networks. J Ambient Intell Humaniz Comput 6(2):193–205

    Article  Google Scholar 

  • Giuseppe G, Jussi P, Ville A, Jani M (2015) Evaluating context-aware user interface migration in multi-device environments. J Ambient Intell Humaniz Comput 6(2):259–277

    Article  Google Scholar 

  • Hyvönen E, Viljanen K, Suominen O (2007) HealthFinland—finish health information on the Semantic Web. Semant Web 4825:778–791

    Article  Google Scholar 

  • Li Y, Mostafa J (2006) A privacy enhancing infomediary for retrieving personalized health information from the Web. Personal Information Management, pp. 82–85

  • Makazhanov A, Rafiei D, Waqar M (2015) Predicting political preference of Twitter users. J Soc Netw Anal Min 4:193 (May 2014)

    Article  Google Scholar 

  • Matsumoto D, Juang L (2012) Culture and psychology, 5th edn. Cengage Learning Inc, United States

    Google Scholar 

  • Sahay S, Ram A (2011) Socio-semantic health information access. In: Proceedings of the AAAI Spring Symposium on AI and Health Communication. http://www.aaai.org/ocs/index.php/SSS/SSS11/paper/download/2450/2855. Accessed 26 May 2014

  • Shumei Z, Paul M, Chris N, Huiru Z, Norman B (2013) An ontological framework for activity monitoring and reminder reasoning in an assisted environment. J Ambient Intell Humaniz Comput 4(2):157–168

    Article  Google Scholar 

  • Suominen O et al (2009) Web semantics. World Wide Web Internet Web Inf Syst 7:287–297

    Google Scholar 

  • Thangaraj M, Chamundeeswari M (2011) A survey of agent-based personalized semantic information retrieval. IJCST 2(3):488–498

    Google Scholar 

  • Wang Y, Liu Z (2005) Personalized health information retrieval system. In: Annual Symposium proceedings, p. 1149. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1560474&tool=pmcentrez&rendertype=abstract

Download references

Acknowledgments

The authors would like to acknowledge the support provided by King Abdulaziz City for Science and Technology (KACST) through the Science and Technology Unit at King Fahd University of Petroleum and Minerals for funding this work (project No.10-INF1381-04) as part of the National Science, Technology and Innovation Plan.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tarek Helmy.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Helmy, T., Al-Nazer, A. Semantic manipulation of user’s queries and modeling the health and nutrition preferences. J Ambient Intell Human Comput 6, 391–405 (2015). https://doi.org/10.1007/s12652-015-0293-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-015-0293-8

Keywords

Navigation