Government-to-Business personalized e-services using semantic-enhanced recommender system

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6866 LNCS, Issue , 2011, Pages 197-211

  Shambour, Qusai ^a   Lu, Jie ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

e Government; Government to Business e Service; Item based Collaborative Filtering; Recommender Systems; Semantic Filtering

Indexed keywords

BUSINESS PARTNERS; COLD-START; COLLABORATIVE FILTERING; DATA SETS; E-GOVERNMENT; E-GOVERNMENT SERVICES; E-GOVERNMENTS; E-SERVICES; EFFECTIVE SOLUTION; INFORMATION OVERLOADS; ITEM-BASED CF; ITEM-BASED COLLABORATIVE FILTERING; SEMANTIC FILTERING; E- SERVICES; GOVERNMENT TO BUSINESS;

GOVERNMENT DATA PROCESSING; INFORMATION SYSTEMS; RECOMMENDER SYSTEMS; SEMANTICS; BISMUTH COMPOUNDS; IGNITION; INFORMATION SERVICES; SELENIUM COMPOUNDS; STARTING;

INFORMATION SERVICES; COLLABORATIVE FILTERING;

EID: 80052377774     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-22961-9_16     Document Type: Conference Paper

References (27)

1. Evans, D., Yen, D.C.: E-Government: Evolving Relationship of Citizens and Government, Domestic, and International Development. Government Information Quarterly 23(2), 207-235 (2006)
2. Lu, J., Shambour, Q., Xu, Y., Lin, Q., Zhang, G.: Bizseeker: A Hybrid Semantic Recommendation System for Personalized Government-To-Business E-Services. Internet Research 20(3), 342-365 (2010)
3. Zhang, L., Zhu, M., Huang, W.: A Framework for an Ontology-Based E-Commerce Product Information Retrieval System. Journal of Computers 4(6), 436-443 (2009)
4. Adomavicius, G., Tuzhilin, A.: Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734-749 (2005)
5. Burke, R.: Hybrid Web Recommender Systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web 2007. LNCS, vol. 4321, pp. 377-408. Springer, Heidelberg (2007)
6. Herlocker, J., Konstan, J.A., Riedl, J.: An Empirical Analysis of Design Choices in Neighborhood-based Collaborative Filtering Algorithms. Information Retrieval 5(4), 287-310 (2002)
7. Hung, L.: A Personalized Recommendation System based on Product Taxonomy for One-to-One Marketing Online. Expert Systems with Applications 29(2), 383-392 (2005)
8. Schafer, J.B., Konstan, J.A., Riedl, J.: E-commerce Recommendation Applications. Data Mining and Knowledge Discovery 5(1), 115-153 (2001)
9. Drachsler, H., Hummel, H., Koper, R.: Identifying the Goal, User Model and Conditions of Recommender Systems for Formal and Informal Learning. Journal of Digital Information 10(2), 4-24 (2009)
10. Guo, X., Lu, J.: Intelligent e-Government Services with Personalized Recommendation Techniques. International Journal of Intelligent Systems 22(5), 401-417 (2007)
11. Adomavicius, G., Tuzhilin, A.: Personalization Technologies: A Process-Oriented Perspective. Communications of the ACM 48(10), 83-90 (2005)
12. Ronaghan, S.A.: Benchmarking E-Government: A Global Perspective, Assessing the Progress of the UN Member States (2002), http://unpan1.un.org/ intradoc/groups/public/documents/un/unpan021547.pdf
13. Terán, L., Meier, A.: A Fuzzy Recommender System for eElections. In: Andersen, K., Francesconi, E., Grönlund, Å., van Engers, T. (eds.) EGOVIS 2010. LNCS, vol. 6267, pp. 62-76. Springer, Heidelberg (2010)
14. Layne, K., Lee, J.: Developing Fully Functional e-Government: A Four Stage Model. Government Information Quarterly 18(2), 122-136 (2001)
15. Wauters, P., Nijskens, M., Tiebout, J.: The User Challenge: Benchmarking the Supply of Online Public Services (2007), http://www.ch.capgemini.com/m/ch/ tl/EU-eGovernment-Report-2007
16. Baum, C., Di Maio, A.: Gartner's Four Phases of E-government Model. Gartner Group (2000)
17. Deloitte, T.: The Citizen as Customer. CMA Management 74(10), 58 (2001)
18. Schmidt, K.-U., Stojanovic, L., Stojanovic, N., Thomas, S.: Personalization in E-Government: An Approach that Combines Semantics and Web 2.0. In: Vitvar, T., Peristeras, V., Tarabanis, K. (eds.) Semantic Technologies for E-Government, pp. 261-285. Springer, Heidelberg (2010)
19. Bogerman, E., Smits, L.: Benchmark Personalisation of Governmental eServices for Citizens (2009), http://www.e-overheid.nl/e-overheid-2.0/live/ binaries/pip/bestanden/benchmark-report-definitief-4aug.pdf
20. Grandi, F., Mandreoli, F., Martoglia, R., Ronchetti, E., Scalas, M., Tiberio, P.: Semantic web techniques for personalization of eGovernment services. In: Roddick, J., Benjamins, V.R., Si-said Cherfi, S., Chiang, R., Claramunt, C., Elmasri, R.A., Grandi, F., Han, H., Hepp, M., Lytras, M.D., Mišić, V.B., Poels, G., Song, I.-Y., Trujillo, J., Vangenot, C. (eds.) ER Workshops 2006. LNCS, vol. 4231, pp. 435-444. Springer, Heidelberg (2006)
21. Pasquale De, M., Giovanni, Q., Domenico, U., Giorgio, T.: A Multi-Agent System for the Management of e-Government Services. In: Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology, pp. 718-724. IEEE Press, Washington (2005)
22. Sarwar, B., Karypis, G., Konstan, J., Reidl, J.: Item-based Collaborative Filtering Recommendation Algorithms. In: Proceedings of the 10th International Conference on World Wide Web, pp. 285-295. ACM Press, Hong Kong (2001)
23. Pieterson, W., Ebbers, W., van Dijk, J.: Personalization in the Public Sector: An Inventory of Organizational and User Obstacles Towards Personalization of Electronic Services in the Public Sector. Government Information Quarterly 24(1), 148-164 (2007)
24. Tan, P., Steinbach, M., Kumar, V.: Introduction to Data Mining. Pearson Education Inc., Boston (2006)
25. Candillier, L., Meyer, F., Fessant, F.: Designing specific weighted similarity measures to improve collaborative filtering systems. In: Perner, P. (ed.) ICDM 2008. LNCS (LNAI), vol. 5077, pp. 242-255. Springer, Heidelberg (2008)
26. Shambour, Q., Lu, J.: A Framework of Hybrid Recommendation System for Government-to-Business Personalized e-Services. In: Proceedings of the 7th International Conference on Information Technology: New Generations (ITNG 2010), pp. 592-597. IEEE Press, Las Vegas (2010)
27. Deshpande, M., Karypis, G.: Item-based Top-N Recommendation Algorithms. ACM Transactions on Information Systems 22(1), 143-177 (2004)