Abstract
Situation awareness relies on the situation context, classifying context and inferring further situation about context. However, the relevant applications have to deal with the inherent imperfection of situation recognition for decision making. The current researches of situation-aware focused on situation recognition based on modeling, classifying and apperceiving of context information, which were insufficiency in the researches and utilization in situation relevance. To overcome this deficiency, this paper fully analyzes the situation relevance (including the trigger and dependency among situations) based on situation ontology, and puts forward a situation-aware method based on ontology analysis of the semantic social network (SR-SSNOA). The main research includes that: (1) SR-SSNOA converts the situation ontology into different figures, and introduces semantic social network to analyze situation ontology. (2) SR-SSNOA realizes the recognition and recommendation of situation by synthetically considering the situation quality, the situation relevance and the community impact. Extensive experiments are carried out, which reveals the performance of SR-SSNOA at different parameter values. A questionnaire is conducted to evaluate the results, which further proves our method’s accuracy and correctness.
Change history
29 March 2019
The authors have retracted this chapter [1] because the method described in the chapter is based on the wrong data set, which means that the experimental results cannot be reproduced. All authors agree with this retraction.
References
Jung, Y., Ryu, J., Kim, K.M., Myaeng, S.H.: Automatic construction of a large-scale situation ontology by mining how-to instructions from the web. Web Semantics: Science, Services and Agents on the World Wide Web 8(2), 110–124 (2010)
WeiĂŸenberg, N., Gartmann, R., Voisard, A.: An ontology-based approach to personalized situation-aware mobile service supply. GeoInformatica 10(1), 55–90 (2006)
Stan, J., Egyed-Zsigmond, E., Joly, A., Maret, P.: A user profile ontology for situation-aware social networking. In: 3rd Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI 2008) (2008)
Chen, H., Finin, T., Joshi, A.: An ontology for context-aware pervasive computing environments. The Knowledge Engineering Review 18(03), 197–207 (2003)
Kim, M., Kim, M.: A formal definition of situation towards situation-aware computing. In: Lytras, M.D., Damiani, E., Carroll, J.M., Tennyson, R.D., Avison, D., Naeve, A., Dale, A., Lefrere, P., Tan, F., Sipior, J., Vossen, G. (eds.) WSKS 2009. LNCS, vol. 5736, pp. 553–563. Springer, Heidelberg (2009)
Downes, S.: Semantic networks and social networks. The Learning Organization 12(5), 411–417 (2005)
Wang, L., Hu, G.X.: P2P semantic community model based on interest and trust evaluation. Computer Engineering 13, 007 (2009)
Davoodi, E., Kianmehr, K., Afsharchi, M.: A semantic social network-based expert recommender system. Applied Intelligence, 1–13 (2013)
Hoser, B., Hotho, A., Jäschke, R., Schmitz, C., Stumme, G.: Semantic network analysis of ontologies. In: Sure, Y., Domingue, J. (eds.) ESWC 2006. LNCS, vol. 4011, pp. 514–529. Springer, Heidelberg (2006)
wikiHow. http://www.wikihow.com/Main-Page (accessed May 1, 2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Hu, W., Wang, H. (2015). RETRACTED CHAPTER: A Situation-Aware Method Based on Ontology Analysis of the Semantic Social Network. In: Zhang, S., Wirsing, M., Zhang, Z. (eds) Knowledge Science, Engineering and Management. KSEM 2015. Lecture Notes in Computer Science(), vol 9403. Springer, Cham. https://doi.org/10.1007/978-3-319-25159-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-25159-2_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25158-5
Online ISBN: 978-3-319-25159-2
eBook Packages: Computer ScienceComputer Science (R0)