Service Recommendation on Wiki-WS Platform

• Autorzy: Sobecki A.
• Języki publikacji: EN

Abstrakty

EN

The article presents the issues of recommendation services for users. The commonly used solutions shown include known classes of recommendation systems and information about their area of use and the most frequently used algorithms. The issue of choosing the services has been described based on the Wiki-WS platform including a model of cooperation with the recommendation system. The conclusion from the analysis of the proposed model and available algorithms is that there is a need to create a hybrid service recommendation algorithm in order to fulfill the requirements of those using a service platform like Wiki-WS.

Słowa kluczowe

EN

recommendation system; Wiki-WS; web services; web platform; recommendation algorithms

• Wydawca: Politechnika Gdańska
• Czasopismo: TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk
• Rocznik: 2015
• Tom: Vol. 19, No 4
• Strony: 445--453
• Opis fizyczny: Bibliogr. 17 poz., rys., tab.

Twórcy

autor

Sobecki A.

• Academic Computer Centre, Gdansk University of Technology, Narutowicza 11/12, 80-233 Gdansk, Poland

Bibliografia

• [1] Krawczyk H and Downar M 2012 Commonly Accessible Web Service Platform – WikiWS, Intelligent Tools for Building a Scientific Information Platform, Springer 251
• [2] Goldberg G, Nichols D, Oki B M and Terry D 1992 Communication ACM 35 61
• [3] Mahmood T and Ricci F 2009 Improving recommender systems with adaptive conversational strategies, ACM 73
• [4] Burke R 2007 Hybrid web recommender systems, The Adaptive Web 377
• [5] Ricci F, Rokach L and Shapira B 2011 Introduction to Recommender Systems Handbook, Springer 1
• [6] Frakes W 1992 Information Retrieval Data Structures and Algorithms, Prentice-Hall
• [7] Fayyad U, Piatetsky-Shapiro G and Smyth P 1996 American Assocation for Artifical Intelligence Magazine 37
• [8] Witten I H and Eibe F 2005 Data Mining: Practical machine learning tools and techniques, Morgan Kaufmann
• [9] Pazzani M J and Billsus D 2007 Content-based recommendation systems, The adaptive web, Springer 325
• [10] Bridge D, G¨oker M, McGinty L and Smyth B 2006 The Knowledge Engineering review 3 (20) 315
• [11] Schafer J B, Frankowski D, Herlocker J and Sen S 2007 Collaborative filtering recommender systems, The Adaptive Web, Springer 291
• [12] Kamahara J, Asakawa T, Shimojo S and Miyahara H 2005 A community-based recommendation system to reveal unexpected interests, Proceedings of the 11th International Multimedia Modelling Conference (MMM 2005) 433
• [13] Pazzani M J 1999 Artificial Intelligence Review 13 (5–6) 393
• [14] Adomavicius G and Tuzhilin A 2005 IEEE Transactions on Knowledge and Data Engineering 17 (6) 734
• [15] Herlocker J L, Konstan J A, Terveen L G and Riedl J T 2004 ACM Transactionall Information Systems 22 (1) 5
• [16] Sobecki A 2015 Hybrydowy system rekomendujący usługi do scenariuszy aplikacji wszechobecnych, PhD Dissertation
• [17] Krawczyk H and Proficz J 2010 Kaskada-multimedia processing platform architecture, Proceedings of the 2010 International Conference on Signal Processing and Multimedia Applications (SIGMAP) 26