scholarly journals QoS Prediction for Neighbor Selection via Deep Transfer Collaborative Filtering in Video Streaming P2P Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Wenming Ma ◽  
Qian Zhang ◽  
Chunxiao Mu ◽  
Meng Zhang
Keyword(s):  
Collaborative Filtering ◽  
Video Streaming ◽  
Historical Data ◽  
Experimental Studies ◽  
The Other ◽  
P2p Networks ◽  
P2p Streaming ◽  
Qos Prediction ◽  
The Past ◽  
Qos Evaluation

To expand the server capacity and reduce the bandwidth, P2P technologies are widely used in video streaming systems in recent years. Each client in the P2P streaming network should select a group of neighbors by evaluating the QoS of the other nodes. Unfortunately, the size of video streaming P2P network is usually very large, and evaluating the QoS of all the other nodes is resource-consuming. An attractive way is that we can predict the QoS of a node by taking advantage of the past usage experiences of a small number of the other clients who have evaluated this node. Therefore, collaborative filtering (CF) methods could be used for QoS evaluation to select neighbors. However, we might use different QoS properties for different video streaming policies. If a new video steaming policy needs to evaluate a new QoS property, but the historical experiences include very few evaluation data for this QoS property, CF methods would incur severe overfitting issues, and the clients then might get unsatisfied recommendation results. In this paper, we proposed a novel neural collaborative filtering method based on transfer learning, which can evaluate the QoS with few historical data by evaluating the other different QoS properties with rich historical data. We conduct our experiments on a large real-world dataset, the QoS values of which are obtained from 339 clients evaluating on the other 5825 clients. The comprehensive experimental studies show that our approach offers higher prediction accuracy than the traditional collaborative filtering approaches.

scholarly journals Graph-Based Collaborative Filtering with MLP

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Shengyu Lu ◽  
Hangping Chen ◽  
XiuZe Zhou ◽  
Beizhan Wang ◽  
Hongji Wang ◽  
...  
Keyword(s):  
Collaborative Filtering ◽  
Kernel Function ◽  
Multilayer Perceptron ◽  
Historical Data ◽  
Recommendation Systems ◽  
The Other ◽  
Coefficient Of Correlation ◽  
Other Hand ◽  
Latent Features ◽  
Svd Method

The collaborative filtering (CF) methods are widely used in the recommendation systems. They learn users’ interests and preferences from their historical data and then recommend the items users may like. However, the existing methods usually measure the correlation between users by calculating the coefficient of correlation, which cannot capture any latent features between users. In this paper, we proposed an algorithm based on graph. First, we transform the users’ information into vectors and use SVD method to reduce dimensions and then learn the preferences and interests of all users based on the improved kernel function and map them to the network; finally, we predict the user’s rating for the items through the Multilayer Perceptron (MLP). Compared with existing methods, on one hand, our method can discover some latent features between users by mapping users’ information to the network. On the other hand, we improve the vectors with the ratings information to the MLP method and predict the ratings for items, so we can achieve better effects for recommendation.

scholarly journals General Collaborative Filtering for Web Service QoS Prediction

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Wenming Ma ◽  
Rongjie Shan ◽  
Mingming Qi
Keyword(s):  
Collaborative Filtering ◽  
Web Service ◽  
Matrix Factorization ◽  
Experimental Studies ◽  
Low Rank ◽  
Qos Prediction ◽  
Latent Vector ◽  
Wide Range ◽  
Regularization Techniques ◽  
Low Dimensional

To avoid the expensive and time-consuming evaluation, collaborative filtering (CF) methods have been widely studied for web service QoS prediction in recent years. Among the various CF techniques, matrix factorization is the most popular one. Much effort has been devoted to improving matrix factorization collaborative filtering. The key idea of matrix factorization is that it assumes the rating matrix is low rank and projects users and services into a shared low-dimensional latent space, making a prediction by using the dot product of a user latent vector and a service latent vector. Unfortunately, unlike the recommender systems, QoS usually takes continuous values with very wide range, and the low rank assumption might incur high bias. Furthermore, when the QoS matrix is extremely sparse, the low rank assumption also incurs high variance. To reduce the bias, we must use more complex assumptions. To reduce the variance, we can adopt complex regularization techniques. In this paper, we proposed a neural network based framework, named GCF (general collaborative filtering), with the dropout regularization, to model the user-service interactions. We conduct our experiments on a large real-world dataset, the QoS values of which are obtained from 339 users on 5825 web services. The comprehensive experimental studies show that our approach offers higher prediction accuracy than the traditional collaborative filtering approaches.

scholarly journals Employing opposite ratings users in a new approach to collaborative filtering

2022 ◽  
Vol 25 (1) ◽  
pp. 450
Author(s):  
Abdellah El Fazziki ◽  
Yasser El Madani El Alami ◽  
Jalil Elhassouni ◽  
Ouafae El Aissaoui ◽  
Mohammed Benbrahim
Keyword(s):  
Collaborative Filtering ◽  
Basic Assumption ◽  
Recommendation System ◽  
Experimental Results ◽  
The Other ◽  
Unusual Behavior ◽  
New Approach ◽  
The Real ◽  
The Past ◽  
The One

Over the past few decades, various recommendation system paradigms have been developed for both research and industrial purposes to satisfy the needs and preferences of users when they deal with enormous data. The collaborative filtering (CF) is one of the most popular recommendation techniques, although it is still immature and suffers from some difficulties such asparsity, gray sheep and scalability impeding recommendation quality. Therefore, we propose a new CF approach to deal with the gray sheep problem in order to improve the predictions accuracy. To realize this goal, our solution aims to infer new users from real ones existing in datasets. This transformation allows for creating users with opposite preferences to the real ones. On the one hand, our approach permits to amplify the number of neighbors, especially in the case of users who have unusual behavior (gray sheep). On the other hand, it facilitates building a dense similar neighborhood. The basic assumption behind this is that if user X is not similar to user Y, then the imaginary user ¬X is similar to the user Y. The performance of our approach was evaluated using two datasets, MovieLens and FilmTrust. Experimental results have shown that our approach surpasses many traditional recommendation approaches.

scholarly journals New Zealand

2019 ◽  
Vol 19 (163) ◽  
pp. 1
Author(s):  
Keyword(s):  
New Zealand ◽  
Central Bank ◽  
Technical Assistance ◽  
Historical Data ◽  
The Other ◽  
The Past ◽  
Standardized Report ◽  
Reserve Bank ◽  
Source Data

At the request of the Reserve Bank of New Zealand (RBNZ), and with the support of the IMF’s Asia & Pacific Department (APD), a monetary and financial statistics (MFS) technical assistance (TA) mission visited Wellington, New Zealand during October 1–12, 2018.1 The mission’s main objectives were to assist the RBNZ to: (i) complete the central bank Standardized Report Form (SRF 1SR); (ii) review the source data and bridge table used to produce Other Depository Corporations (ODCs) Standardized Report Form (SRF 2SR);(iii) assist the RBNZ to produce additional historical data in the SRFs 1SR and 2SR for the past five years; (iv) review the available source data for the compilation the Other Financial Corporations (OFCs) Standardized Report Form (SRF 4SR); (v) prepare metadata for the central bank, ODC, and OFC surveys; and (vi) agree on a timetable for RBNZ’s SRF-reporting of its MFS.

Immunoferritin localization of intracellular antigens in positively stained frozen sections

1978 ◽  
Vol 36 (2) ◽  
pp. 168-169
Author(s):  
K. T. Tokuyasu
Keyword(s):  
Surface Tension ◽  
Water Surface ◽  
Thin Layers ◽  
The Other ◽  
Positive Staining ◽  
Frozen Sections ◽  
The Past ◽  
Ultrathin Frozen Sections ◽  
Definition Of

During the past investigations of immunoferritin localization of intracellular antigens in ultrathin frozen sections, we found that the degree of negative staining required to delineate u1trastructural details was often too dense for the recognition of ferritin particles. The quality of positive staining of ultrathin frozen sections, on the other hand, has generally been far inferior to that attainable in conventional plastic embedded sections, particularly in the definition of membranes. As we discussed before, a main cause of this difficulty seemed to be the vulnerability of frozen sections to the damaging effects of air-water surface tension at the time of drying of the sections.Indeed, we found that the quality of positive staining is greatly improved when positively stained frozen sections are protected against the effects of surface tension by embedding them in thin layers of mechanically stable materials at the time of drying (unpublished).

Applications of Through-Focus Dark Field Image Shifts to Phase Identification

1975 ◽  
Vol 33 ◽  
pp. 178-179
Author(s):  
Prakash Rao
Keyword(s):  
Dark Field Image ◽  
Thin Foil ◽  
Dark Field ◽  
The Other ◽  
Stereo Image ◽  
Phase Identification ◽  
The Past ◽  
Field Electron Microscopy ◽  
Dark Field Electron ◽  
Recent Extension

Image shifts in out-of-focus dark field images have been used in the past to determine, for example, epitaxial relationships in thin films. A recent extension of the use of dark field image shifts has been to out-of-focus images in conjunction with stereoviewing to produce an artificial stereo image effect. The technique, called through-focus dark field electron microscopy or 2-1/2D microscopy, basically involves obtaining two beam-tilted dark field images such that one is slightly over-focus and the other slightly under-focus, followed by examination of the two images through a conventional stereoviewer. The elevation differences so produced are usually unrelated to object positions in the thin foil and no specimen tilting is required.In order to produce this artificial stereo effect for the purpose of phase separation and identification, it is first necessary to select a region of the diffraction pattern containing more than just one discrete spot, with the objective aperture.

Effects of Attachment Styles on the Experience of Equity in Heterosexual Couples Relationships

2003 ◽  
Vol 50 (4) ◽  
pp. 298-310 ◽  
Author(s):  
Ina Grau ◽  
Jörg Doll
Keyword(s):  
Attachment Theory ◽  
Attachment Style ◽  
Intimate Relationships ◽  
Attachment Styles ◽  
Experimental Studies ◽  
The Other ◽  
Heterosexual Couples ◽  
Secure Attachment ◽  
Dependent Variables ◽  
Equity Ratio

Abstract. Employing one correlational and two experimental studies, this paper examines the influence of attachment styles (secure, anxious, avoidant) on a person’s experience of equity in intimate relationships. While one experimental study employed a priming technique to stimulate the different attachment styles, the other involved vignettes describing fictitious characters with typical attachment styles. As the specific hypotheses about the single equity components have been developed on the basis of the attachment theory, the equity ratio itself and the four equity components (own outcome, own input, partner’s outcome, partner’s input) are analyzed as dependent variables. While partners with a secure attachment style tend to describe their relationship as equitable (i.e., they give and take extensively), partners who feel anxious about their relationship generally see themselves as being in an inequitable, disadvantaged position (i.e., they receive little from their partner). The hypothesis that avoidant partners would feel advantaged as they were less committed was only supported by the correlational study. Against expectations, the results of both experiments indicate that avoidant partners generally see themselves (or see avoidant vignettes) as being treated equitably, but that there is less emotional exchange than is the case with secure partners. Avoidant partners give and take less than secure ones.

‘Newness which never perishes’? Schoenberg’s ambivalent reception of Haydn

2010 ◽  
Vol 51 (1-2) ◽  
pp. 215-224
Author(s):  
Alexander Carpenter
Keyword(s):  
The Other ◽  
Major Influence ◽  
Musical Style ◽  
The Past ◽  
Other Hand ◽  
The Future ◽  
Music Tradition

This paper explores Arnold Schoenberg’s curious ambivalence towards Haydn. Schoenberg recognized Haydn as an important figure in the German serious music tradition, but never closely examined or clearly articulated Haydn’s influence and import on his own musical style and ethos, as he did with many other major composers. This paper argues that Schoenberg failed to explicitly recognize Haydn as a major influence because he saw Haydn as he saw himself, namely as a somewhat ungainly, paradoxical figure, with one foot in the past and one in the future. In his voluminous writings on music, Haydn is mentioned by Schoenberg far less frequently than Bach, Mozart, or Beethoven, and his music appears rarely as examples in Schoenberg’s theoretical texts. When Schoenberg does talk about Haydn’s music, he invokes — with tacit negativity — its accessibility, counterpoising it with more recondite music, such as Beethoven’s, or his own. On the other hand, Schoenberg also praises Haydn for his complex, irregular phrasing and harmonic exploration. Haydn thus appears in Schoenberg’s writings as a figure invested with ambivalence: a key member of the First Viennese triumvirate, but at the same time he is curiously phantasmal, and is accorded a peripheral place in Schoenberg’s version of the canon and his own musical genealogy.

Economic Performance and Public Finance in Kenya, 1960-2010

2018 ◽  
Vol 47 (2) ◽  
Author(s):  
Kempe Ronald Hope
Keyword(s):  
Public Finance ◽  
Economic Performance ◽  
Emerging Economy ◽  
The Other ◽  
Government Investment ◽  
The Past ◽  
Other Hand ◽  
Private Savings ◽  
Per Capita ◽  
Real Growth

Countries with positive per capita real growth are characterised by positive national savings—including government savings, increases in government investment, and strong increases in private savings and investment. On the other hand, countries with negative per capita real growth tend to be characterised by declines in savings and investment. During the past several decades, Kenya’s emerging economy has undergone many changes and economic performance has been epitomised by periods of stability, decline, or unevenness. This article discusses and analyses the record of economic performance and public finance in Kenya during the period 1960‒2010, as well as policies and other factors that have influenced that record in this emerging economy. 

Sign in / Sign up

Export Citation Format

Share Document