By James J. (Jong Hyuk) Park, Gangman Yi, Young-Sik Jeong, Hong Shen
This publication includes the mixed complaints of the 4th overseas convention on Ubiquitous Computing program and instant Sensor community (UCAWSN-15) and the sixteenth overseas convention on Parallel and allotted Computing, purposes and applied sciences (PDCAT-15). The mixed lawsuits current peer-reviewed contributions from educational and commercial researchers in fields together with ubiquitous and context-aware computing, context-awareness reasoning and illustration, position expertise prone, and architectures, protocols and algorithms, power, administration and keep watch over of instant sensor networks. The ebook comprises the newest learn effects, sensible advancements and purposes in parallel/distributed architectures, instant networks and cellular computing, formal tools and programming languages, community routing and verbal exchange algorithms, database purposes and information mining, entry keep watch over and authorization and privateness holding computation.
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In: Proceedings of the 22nd international conference on World Wide Web. International World Wide Web Conferences Steering Committee, Rio de Janeiro, pp 781–802 5. Ma H et al (2011) Recommender systems with social regularization. Wsdm, pp 287–296 6. Meng J et al (2014) Scalable recommendation with social contextual information. IEEE Trans Knowl Data Eng 26(11):2789–2802 7. Xiwang Y, Harald S Yong L (2012) Circle-based recommendation in online social networks. In: Proceedings of the 18th ACM SIGKDD international conference on knowledge discovery and data mining %@ 978-1-4503-1462-6.
To use them in the MF-based RS, we come up with two kinds of social regularization for each similarity function. Compared with previous social regularization, our methods can more precisely explain users’ interest similarity. The experimental analysis on a large dataset shows that our approaches improve the performance of the state-of-the-art social recommendation model. Keywords Recommender system regularization Á Social network Á Matrix factorization Á Social Z. cn H. cn H. (Jong Hyuk) Park et al.
This is because of two reasons; the index computation is easy and cache miss rate is fewer in the proposed scheme. 2 Generalized Two Dimensional Representation (G2A) Scheme We propose an algorithm to represent an n dimensional array by a 2 dimensional array. Let A[l1] [l2]… [ln] be a Traditional Multidimensional Array (TMA(n)) of size [l1, l2,…,ln] and hx1 ; x2 ; . ; xn i be the subscripts of the array A; where l1, l2,…,ln is the length of dimension d1, d2,…, dn and xi = 0, 1…, (li − 1) (1 ≤ i ≤ n).
