Trust-based Modelling of Multi-criteria Crowdsourced Data
Tóm tắt
Từ khóa
Tài liệu tham khảo
Adomavicius G, Kwon Y (2007) New recommendation techniques for multicriteria rating systems. IEEE Intell Syst 22(3):48–55
Adomavicius G, Kwon Y (2015) Multi-criteria recommender systems. In: Recommender systems handbook, chapter 24. Springer, Berlin, pp 847–880
Amatriain X (2013) Mining large streams of user data for personalized recommendations. ACM SIGKDD Explor Newsl 14(2):37–48
Bilge A, Kaleli C (2014) A multi-criteria item-based collaborative filtering framework. In: JCSSE 2014, Pattaya, May. IEEE, pp 18–22
Breese JS, Heckerman D, Kadie C (1998) Empirical analysis of predictive algorithms for collaborative filtering. In: UAI’98, Madison, July 1998. Morgan Kaufmann, pp 43–52
Cremonesi P, Koren Y, Turrin R (2010) Performance of recommender algorithms on top-n recommendation tasks. In: RecSys’10, Barcelona, September. ACM, pp 39–46
Davoudi A, Chatterjee M (2016) Modeling trust for rating prediction in recommender systems. In: MLRec 2016, Miami, May. SIAM, pp 1–8
Ebadi A, Krzyzak A (2016) A hybrid multi-criteria hotel recommender system using explicit and implicit feedbacks. Int J Comput Electr Autom Control Inf Eng 10(8):1377–1385
Egger R, Gula I, Walcher D (2016) Open Tour Open Innov. Crowdsourcing and co-creation challenging the tourism industry, Springer, Berlin
Ekstrand MD, Riedl JT, Konstan JA et al (2011) Collaborative filtering recommender systems. Found Trends Hum Comput Interact 4(2):81–173
Farokhi N, Vahid M, Nilashi M, Ibrahim O (2016) A multi-criteria recommender system for tourism using fuzzy approach. J Soft Comput Decis Support Syst 3(4):19–29
Fuchs M, Zanker M (2012) Multi-criteria ratings for recommender systems: an empirical analysis in the tourism domain. In: EC-Web 2012, Vienna, September. Springer, pp 100–111
Gama J (2010) Knowledge discovery from data streams. Data mining and knowledge discovery series. CRC Press, Boca Raton
Gama J, Sebastião R, Rodrigues PP (2009) Issues in evaluation of stream learning algorithms. In: KDD’09, Paris, June. ACM, pp 329–338
Herlocker JL, Konstan JA, Terveen LG, Riedl JT (2004) Evaluating collaborative filtering recommender systems. ACM Trans Inf Syst 22(1):5–53
Jannach D et al (2012) Recommending hotels based on multi-dimensional customer ratings. Information and communication technologies in tourism. Springer, Helsingborg, pp 320–331
Jhalani T, Kant V, Dwivedi P (2016) A linear regression approach to multi-criteria recommender system. In: DMBD 2016, volume 9714 of LNCS, Bali, June. Springer, pp 235–243
Jia D, Zhang F, Liu S (2013) A robust collaborative filtering recommendation algorithm based on multidimensional trust model. J Softw 8(1):11–18
Jøsang A, Ismail R, Boyd C (2007) A survey of trust and reputation systems for online service provision. Decis Support Syst 43(2):618–644
Lathia N, Hailes S, Capra L (2008) Trust-based collaborative filtering. In: IFIP international conference on trust management, volume 263 of trust management II, Boston. Springer, pp 119–134
Leal F, Dias JM, Malheiro B, Burguillo JC (2016) Analysis and visualisation of crowd-sourced tourism data. In: C3S2E’16, Porto, July. ACM, pp 98–101
Leal F, Malheiro B, Burguillo JC (2017) Prediction and analysis of hotel ratings from crowd-sourced data, volume 570 of advances in intelligent systems and computing, vol 570. Springer, Madeira, pp 493–502
Lee HH, Teng WG (2007) Incorporating multi-criteria ratings in recommendation systems. In: IRI 2007, Las Vegas, August. IEEE, pp 273–278
Linden G, Smith B, York J (2003) Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Comput 7(1):76–80
Liu L, Mehandjiev N, Xu DL (2011) Multi-criteria service recommendation based on user criteria preferences. In: RecSys’11, Chicago, October. ACM, pp 77–84
Manouselis N, Costopoulou C (2007) Analysis and classification of multi-criteria recommender systems. World Wide Web 10(4):415–441
Nilashi M, Bin Ibrahim O, Ithnin N, Sarmin NH (2015) A multi-criteria collaborative filtering recommender system for the tourism domain using expectation maximization (EM) and PCA-ANFIS. Electron Commer Res Appl 14(6):542–562
Randall Brandt D (1988) How service marketers can identify value-enhancing service elements. J Serv Mark 2(3):35–41
Sayed-Mouchaweh M (2016) Learning from data streams in dynamic environments. SpringerBriefs in applied sciences and technology. Springer, Heidelberg
Shambour Q, Hourani M, Fraihat S (2016) An item-based multi-criteria collaborative filtering algorithm for personalized recommender systems. Int J Adv Comput Sci Appl 7(8):275–279
Sykes AO (2000) An introduction to regression analysis. In: Posner EA (ed) Chicago lectures in law and economics. Foundation Press, New York
Takács G, Pilászy I, Németh B, Tikk D (2009) Scalable collaborative filtering approaches for large recommender systems. J Mach Learn Res 10:623–656
Veloso B, Malheiro B, Burguillo JC, Foss J (2017) Personalised fading for stream data. In: SAC 2017, Marrakech, April. ACM, pp 870–872
Wang H, Lu Y, Zhai C (2010) Latent aspect rating analysis on review text data: a rating regression approach. In: KDD’10, Washington, July. ACM, pp 783–792