This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Adomavicius, G., & Tuzhilin, A. (2011). Context-aware recommender systems. In Recommender Systems Handbook (pp. 217-253). Springer US.10.1007/978-0-387-85820-3_7Search in Google Scholar
Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. Knowledge and Data Engineering, IEEE Transactions on, 17(6), 734-749.10.1109/TKDE.2005.99Search in Google Scholar
Al-Mubaid, H., & Nguyen, H.A. (2006). Using MEDLINE as standard corpus for measuring semantic similarity of concepts in the biomedical domain, In Proc. of the IEEE 6th Symposium on Bioinformatics and Bioengineering, (pp. 315-318).10.1109/BIBE.2006.253295Search in Google Scholar
Aydoğan, R., & Yolum, P. (2007, May). Learning consumer p
REFERENCES using semantic similarity. In Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (p. 229). ACM.10.1145/1329125.1329401Search in Google Scholar
Bandara, A., Payne, T., De Roure, D., & Lewis, T. (2007). A semantic approach for service matching in pervasive environments. Technical Report Number: ECSTR-IAM07-006, University of Southampton.Search in Google Scholar
Benazzouz, Y. (2012). Découverte de contexte pour une adaptation automatique de services en intelligence ambiante. Doctoral dissertation, Ecole Nationale superieure de mines, Saint- Etienne, France.Search in Google Scholar
Bisson, G. (2000), La similarite: Une notion symbolique/numerique. IMAG-CNRS, Projet SHERPA, Unité de recherche INRIA Rhone-Alpes, (p. 3).Search in Google Scholar
Broens, T., Pokraev, S., Van Sinderen, M., Koolwaaij, J., & Costa, P. D. (2004). Context- aware, ontology-based service discovery. In Ambient Intelligence (pp. 72-83). Springer Berlin Heidelberg.10.1007/978-3-540-30473-9_7Search in Google Scholar
Bulskov H., Knappe R., & Andreasen T. (2002). On measuring similarity for conceptual querying. In the Proc. of the 5th Int’l Conf. on Flexible Query Answering Systems (pp. 100-111). Springer-Verlag.10.1007/3-540-36109-X_8Search in Google Scholar
Capra, L., Emmerich, W., & Mascolo, C. (2001). Reflective middleware solutions for context-aware applications. In Metalevel Architectures and Separation of Crosscutting Concerns (pp. 126-133). Springer Berlin Heidelberg.10.1007/3-540-45429-2_10Search in Google Scholar
Chang, J., & Song, J. (2012, May). Research on context-awareness service adaptation mechanism in IMS under ubiquitous network. In Vehicular Technology Conference (VTC Spring), 2012 IEEE 75th (pp. 1-5). IEEE.Search in Google Scholar
Chen, A. (2005). Context-aware collaborative filtering system: Predicting the user’s preference in the ubiquitous computing environment. In Location-and Context-Awareness (pp. 244-253). Springer Berlin Heidelberg.10.1007/11426646_23Search in Google Scholar
Dalmau, M., Roose, P., & Laplace, S. (2009). Context-aware adaptable applications: A global approach. International Journal of Computer Science Issues, Vol.1, (pp. 13-25).Search in Google Scholar
d’Amato, Claudia (2007). Similarity-based learning methods for the semantic web, PhD thesis, Universita Degli Studi di Bari Faculta di Scienze Dipartimento di Informatica, pp 97 .Search in Google Scholar
d’Amato, C., Fanizzi, N., & Esposito, F. (2009). A semantic similarity measure for expressive description logics. Universita Degli Studi di Bari Faculta di Scienze Dipartimento di Informatica arXiv preprint arXiv:0911.5043.Search in Google Scholar
Dey, A.K. (2001). Understanding and using context. College of Computing & GVU Center, Georgia Institute of Technology, Atlanta,Personal and Ubiquitous Computing, Vol.5, (pp. 4-7).10.1007/s007790170019Search in Google Scholar
Dietze, S., Gugliotta, A., & Domingue, J. (2008). Bridging the gap between mobile application contexts and semantic web resources: Context-aware mobile and ubiquitous computing for enhanced usability: adaptive technologies and applications. Information Science Publishing (IGI Global).Search in Google Scholar
Doulkeridis, C., Loutas, N., & Vazirgiannis, M. (2006). A system architecture for context- aware service discovery. Electr. Notes Theor. Comput. Sci., 146(1), 101-116.10.1016/j.entcs.2005.11.010Search in Google Scholar
Efstratiou, C. (2004). Coordinated adaptation for adaptive context-aware applications. Doctoral dissertation, Computing Department, Lancaster University, UK, (pp. 173).Search in Google Scholar
Ehrig, M., Haase, P., Hefke, M., & Stojanovic, N. (2005). Similarity for ontologies-a comprehensive framework. ECIS 2005 Proceedings, 127.Search in Google Scholar
El Sayed, A., Hacid, H., & Zighed, D. (2007). A new context-aware measure for semantic distance using a taxonomy and a text corpus. In Information Reuse and Integration. IEEE International Conference on (pp. 279-284). IEEE.10.1109/IRI.2007.4296634Search in Google Scholar
Ganter, B., & Stumme, G., 2002, Formal concept analysis: Methods and applications in computer science. TU Dresden, http://www.aifb.uni-karlsruhe.de/WBS/gst/FBA03.shtml.Search in Google Scholar
García-Crespo, A., Chamizo, J., Rivera, I., Mencke, M., Colomo-Palacios, R., & Gómez- Berbís, J.M. (2009). SPETA: Social pervasive e-tourism advisor. Telematics and Informatics, 26(3), 306-315.10.1016/j.tele.2008.11.008Search in Google Scholar
Ge, J., & Qiu, Y. (2008). Concept similarity matching based on semantic distance. In Semantics, Knowledge and Grid, 2008. SKG’08. Fourth International Conference on (pp. 380383). IEEE.10.1109/SKG.2008.24Search in Google Scholar
Germán, S. (2010). Adaptation d’architectures logicielles collaboratives dans les environnements ubiquitaires. Contribution à l’interopérabilité par la sémantique. Doctoral dissertation, Systèmes (EDSYS), France.Search in Google Scholar
Gicquel, P.Y (2012). Similarités sémantiques et contextuelles pour l’apprentissage informel en mobilité. RJC EIAH’2012, 45.Search in Google Scholar
Gomaa, W.H., & Fahmy, A.A. (2013). A survey of text similarity approaches. International Journal of Computer Applications, 68(13), 13-18.10.5120/11638-7118Search in Google Scholar
Gonzalez-Castillo, J., Trastour, D., & Bartolini, C. (2001). Description logics for matchmaking of services. HP Laboratories technical report, 265.Search in Google Scholar
Harispe, S., Ranwez, S., Janaqi, S., & Montmain, J.(2013). Semantic measures for the comparison of units of language, concepts or instances from text and knowledge representation analysis, A Comprehensive Survey and a Technical Introduction to Knowledge-based Measures Using Semantic Graph Analysis, LGI2P/EMA Research Center, Parc scientifique, France.Search in Google Scholar
Hartmann, M., Zesch, T., Muhlhauser, M., & Gurevych, I. (2008). Using similarity measures for context-aware user interfaces. In Semantic Computing, 2008 IEEE International Conference on (pp. 190-197). IEEE.10.1109/ICSC.2008.94Search in Google Scholar
Henricksen, K., Indulska, J., & Rakotonirainy, A. (2006). Using context and p
REFERENCES to implement self-adapting pervasive computing applications. Software: Practice and Experience, 36(11-12), 1307-1330.Search in Google Scholar
Hirst, G., & St Onge, D. (1998). Lexical chains as representations of context for the detection and correction of malapropisms. In C. Fellbaum (ed.), WordNet: An Electronic Lexical Database, Cambridge, MA: The MIT Press.Search in Google Scholar
Janowicz, K. (2008). Kinds of contexts and their impact on semantic similarity measurement. In Pervasive Computing and Communications. Sixth Annual IEEE International Conference on (pp. 441-446). IEEE.10.1109/PERCOM.2008.35Search in Google Scholar
Jiang J.J., & Conrath D.W. (1997). Semantic similarity based on corpus statistics and lexical taxonomy. Proceedings of International Conference on Research in Computational Linguistics, August 22-24; Taipei, Taiwan.Search in Google Scholar
Kakousis, K., Paspallis, N., & Papadopoulos, G.A. (2010). A survey of software adaptation in mobile and ubiquitous computing. Enterprise Information Systems, 4(4), 355-389.10.1080/17517575.2010.509814Search in Google Scholar
Kang, S., Kim, D., Lee, Y., Hyun, S.J., Lee, D., & Lee, B. (2007). A semantic service discovery network for large-scale ubiquitous computing environments. ETRI journal, 29(5), 545558.10.4218/etrij.07.0106.0281Search in Google Scholar
Keßler, C. (2007). Similarity measurement in context. In Modeling and Using Context (pp. 277-290). Springer Berlin Heidelberg.10.1007/978-3-540-74255-5_21Search in Google Scholar
Keßler, C., Raubal, M., & Janowicz, K. (2007). The effect of context on semantic similarity measurement. In On the Move to Meaningful Internet Systems: OTM 2007 Workshops (pp. 1274-1284). Springer Berlin Heidelberg.Search in Google Scholar
Kirsch-Pinheiro, M., Vanrompay, Y., & Berbers, Y. (2008). Context-aware service selection using graph matching. In 2nd Non Functional Properties and Service Level Agreements in Service Oriented Computing Workshop (NFPSLA-SOC’08), ECOWS. CEUR Workshop proceedings (Vol. 411).Search in Google Scholar
Kirsch-Pinheiro, M., Villanova-Oliver, M., Gensel, J., & Martin, H. (2006). A personalized and context-aware adaptation process for web-based groupware systems. In 4th International Workshop on Ubiquitous Mobile Information and Collaboration Systems, CAiSE’06 Workshop (pp. 884-898).Search in Google Scholar
Klein, M., & Bernstein, A. (2004). Towards high-precision service retrieval. IEEE Internet Computing, January, 30-36.10.1109/MIC.2004.1260701Search in Google Scholar
Lavirotte, S., Lingrand, D., & Tigli, J.Y. (2005). Définition du contexte: fonctions de coût et méthodes de sélection. In Proceedings of the 2nd French-speaking Conference on Mobility and Ubiquity Computing (pp. 9-12). ACM.10.1145/1102613.1102616Search in Google Scholar
Leacock, C., & Chodorow, M. (1998). Combining local context and WordNet similarity for word sense identification. In WordNet: An Electronic Lexical Database, C. Fellbaum, MIT Press.Search in Google Scholar
Lee, J.S., & Lee, J.C. (2007). Context awareness by case-based reasoning in a music recommendation system. In Ubiquitous Computing Systems (pp. 45-58). Springer Berlin Heidelberg.10.1007/978-3-540-76772-5_4Search in Google Scholar
Li, Q., Zheng, Y., Xie, X., Chen, Y., Liu, W., & Ma, W.Y. (2008). Mining user similarity based on location history. In Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (p. 34). ACM.10.1145/1463434.1463477Search in Google Scholar
Li, Y., Bandar, Z.A., & McLean, D. (2003). An approach for measuring semantic similarity between words using multiple information sources. IEEE Transactions on Knowledge and Data Engineering, 15(4), 871-882.10.1109/TKDE.2003.1209005Search in Google Scholar
Lin, D (1998). An information-theoretic definition of similarity. In Proceedings of the 15th International Conference on Machine Learning, July 24-27 1998; Madison, Wisconsin, USA.Search in Google Scholar
Li, L., & Horrocks, I. (2004). A software framework for matchmaking based on semantic web technology. International Journal of Electronic Commerce, 8(4), 39-60.10.1080/10864415.2004.11044307Search in Google Scholar
Liu, L., Lecue, F., Mehandjiev, N., & Xu, L. (2010). Using context similarity for service recommendation. In Semantic Computing (ICSC), 2010 IEEE Fourth International Conference on (pp. 277-284). IEEE.10.1109/ICSC.2010.39Search in Google Scholar
Liu, Q., Ma, H., Chen, E., & Xiong, H. (2013). A survey of context-aware mobile recommendations. International Journal of Information Technology & Decision Making, 12(1), 139-172.10.1142/S0219622013500077Search in Google Scholar
Maedche, A., & Staab, S. (2002). Measuring similarity between ontologies. In Knowledge Engineering and Knowledge Management: Ontologies and the Semantic Web (pp. 251-263). Springer Berlin Heidelberg.Search in Google Scholar
McGovern, J. (2013). Context similarity evaluation: Inferring how users can collectively collaborate together in a pervasive environment. In Cloud and Green Computing (CGC), 2013 Third International Conference on (pp. 553-557). IEEE.10.1109/CGC.2013.93Search in Google Scholar
Meissen, U., Pfennigschmidt, S., Voisard, A., & Wahnfried, T. (200,). Context-and situation-awareness in information logistics. In Current Trends in Database Technology-EDBT 2004 Workshops (pp. 335-344). Springer Berlin Heidelberg.10.1007/978-3-540-30192-9_33Search in Google Scholar
Meng, L., Huang, R., & Gu, J. (2013). A review of semantic similarity measures in wordnet. International Journal of Hybrid Information Technology, 6(1), 1-12.Search in Google Scholar
Michel, M.D., & Deza, E. (2007). Dictionnaire des distances. In Encyclopedia of Distances.Search in Google Scholar
Mihalcea, R., Corley, C., & Strapparava, C. (2006). Corpus-based and knowledge-based measures of text semantic similarity. In AAAI (Vol. 6, pp. 775-780).Search in Google Scholar
Mokhtar, S.B., Preuveneers, D., Georgantas, N., Issarny, V., & Berbers, Y. (2008). EASY: Efficient semAntic Service discoverY in pervasive computing environments with QoS and context support. Journal of Systems and Software, 81(5), 785-808.10.1016/j.jss.2007.07.030Search in Google Scholar
Moon, H. J., Kim, S., Moon, J., & Lee, E. S. (2008). An Effective data processing method for fast clustering. In Computational Science and its Applications–ICCSA 2008 (pp. 335-347). Springer Berlin Heidelberg.10.1007/978-3-540-69848-7_27Search in Google Scholar
Nicklas, D., & Henricksen, K. (2008). Context modeling and reasoning: Key concepts for Pervasive computing. 5th IEEE Workshop on Context Modeling and Reasoning (CoMoRea’08) @PerCom Hong Kong.Search in Google Scholar
Paolucci, M., Kawamura, T., Payne, T.R., & Sycara, K. (2002). Semantic matching of web services capabilities. Lecture Notes in Computer Science, 2342, 333–347.10.1007/3-540-48005-6_26Search in Google Scholar
Petit, M., (2005). L’informatique contextuelle. Technical Report, South Britany University (UBS), France.Search in Google Scholar
Pirró, G., & Euzenat, J. (2010). A feature and information theoretic framework for semantic similarity and relatedness. In The Semantic Web–ISWC 2010 (pp. 615-630). Springer Berlin Heidelberg.10.1007/978-3-642-17746-0_39Search in Google Scholar
Preuveneers, D., Victor, K., Vanrompay, Y., Rigole, P., Pinheiro, M.K., & Berbers, Y. (2009). Context-aware adaptation in an ecology of applications. Context-Aware Mobile and Ubiquitous Computing for Enhanced Usability: Adaptive Technologies and Applications, 1-25.10.4018/978-1-60566-290-9.ch001Search in Google Scholar
Ramparany, F., Benazzouz, Y., Gadeyne, J., & Beaune, P. (2011). Automated context learning in ubiquitous computing environments. In SSN (pp. 9-21).Search in Google Scholar
Ranganathan, A., Shankar, C., & Campbell, R. (2005). Application polymorphism for autonomic ubiquitous computing. Multiagent and Grid Systems, 1(2), 109-129.10.3233/MGS-2005-1205Search in Google Scholar
Rada, R., Bicknell, H., Mili, E., & Blettner, M (1989). Development and application of a metric on semantic nets. IEEE Transaction on Systems, Man, and Cybernetics, 1(19), 17-30.10.1109/21.24528Search in Google Scholar
Resnik, P (1995). Using information content to evaluate semantic similarity. In Proceedings of the 14th International Joint Conference on Artificial Intelligence, August 20-25; Montréal Québec, Canada.Search in Google Scholar
Rodriguez M.A., & Egenhofer, M.J. (2003). Determining semantic similarity among entity classes from different ontologies. IEEE Transactions on Knowledge and Data Engineering, 15, 442-456.10.1109/TKDE.2003.1185844Search in Google Scholar
Rubinstein, H. & Goodenough, J.B. (1965). Contextual correlates of synonymy. Communications of the ACM, 8(10).10.1145/365628.365657Search in Google Scholar
Ruta, M., Scioscia, F., Di Sciascio, E., & Piscitelli, G. (2012). Semantic matchmaking for location-aware ubiquitous resource discovery. International Journal on Advances in Intelligent Systems, 4(3/4), 113-127.Search in Google Scholar
Sánchez, D., Batet, M., Isern, D., & Valls, A. (2012). Ontology-based semantic similarity: A new feature-based approach. Expert Systems with Applications, 39(9), 7718-7728.10.1016/j.eswa.2012.01.082Search in Google Scholar
Saruladha, K. (2011). Semantic similarity measures for information retrieval systems using ontology. Doctoral dissertation, Department of Computer Science, School of Engineering and Technology, Pondicherry University, chapter 2.Search in Google Scholar
Saruladha, K., Aghila, G., & Raj, S. (2010). A survey of semantic similarity methods for ontology based information retrieval. In Machine Learning and Computing (ICMLC), Second International Conference on (pp. 297-301). IEEE.10.1109/ICMLC.2010.63Search in Google Scholar
Schilit, B., Adams, N., & Want, R. (1994). Context-aware computing applications. In IEEE Workshop on Mobile Computing Systems and Applications . Santa Cruz, CA, US.10.1109/WMCSA.1994.16Search in Google Scholar
Sharma, L., & Gera, A. (2013). A survey of recommendation system: Research challenges. International Journal of Engineering Trends and Technology (IJETT), 4(5), 19891992.Search in Google Scholar
Simonin, J., & Carbonell, N. (2007). Interfaces adaptatives, Adaptation dynamique à l’utilisateur courant. arXiv preprint arXiv:0708.3742.Search in Google Scholar
Sussna M. (1993). Word sense disambiguation for free-text indexing using a massive semantic network. In Proc. of Second Int’l Conf. Information Knowledge Management (CIKM ‘93).10.1145/170088.170106Search in Google Scholar
Thompson, M.S. (2006). Service discovery in pervasive computing environments. Doctoral dissertation, Virginia Polytechnic Institute and State University.Search in Google Scholar
Tversky, A (1977). Features of similarity. Psycological Review, 84(4).10.1037/0033-295X.84.4.327Search in Google Scholar
Van Setten, M., Pokraev, S., & Koolwaaij, J. (2004). Context-aware recommendations in the mobile tourist application COMPASS. In Adaptive Hypermedia and Adaptive Web-based Systems (pp. 235-244). Springer Berlin Heidelberg.10.1007/978-3-540-27780-4_27Search in Google Scholar
Viterbo, J., Mazuel, L., Charif, Y., Endler, M., Sabouret, N., Breitman, K., & Briot, J. (2008). Ambient intelligence: Management of distributed and heterogeneous context knowledge. In CRC Studies in Informatics Series (pp. 1-44). Chapman & Hall.Search in Google Scholar
Wu, Z., & Palmer, M. (1994). Verb semantics and lexical selection. In Proceedings of the 32nd Annual Meeting of the Associations for Computational Linguistics (pp. 133-138).10.3115/981732.981751Search in Google Scholar
Yau, S.S., & Huang D. (2006). Mobile middleware for situation-aware service discovery and coordination. In P. Bellavista and A. Corradi (eds.), Handbook of Mobile Middleware, (pp. 10591088).10.1201/9781420013153.ch39Search in Google Scholar
Zhang, F., Liu, W., & Bi, Y. Review on Wordnet-based ontology construction in China, International Journal on Smart Sensing and Intelligent Systems, vol. 6, No. 2, April 2013.10.21307/ijssis-2017-558Search in Google Scholar
Zhong, J., Zhu, H., Li, J., & Yu, Y. (2002). Conceptual graph matching for semantic search. In Proceedings of the 10th International Conference on Conceptual Structures (ICCS) (pp. 92196). Springer-Verlag, London.10.1007/3-540-45483-7_8Search in Google Scholar
Zouari, M. (2011). Architecture logicielle pour l’adaptation distribuée: Application à la réplication de données. Doctoral dissertation, Université Rennes 1, France.Search in Google Scholar