Reliability of Trust Management Systems in Cloud Computing

Cloud computing is an innovation that conveys administrations like programming, stage, and framework over the web. This computing structure is wide spread and dynamic, which chips away at the compensation per-utilize model and supports virtualization. Distributed computing is expanding quickly among purchasers and has many organizations that offer types of assistance through the web. It gives an adaptable and on-request administration yet at the same time has different security dangers. Its dynamic nature makes it tweaked according to client and supplier’s necessities, subsequently making it an outstanding benefit of distributed computing. However, then again, this additionally makes trust issues and or issues like security, protection, personality, and legitimacy. In this way, the huge test in the cloud climate is selecting a perfect organization. For this, the trust component assumes a critical part, in view of the assessment of QoS and Feedback rating. Nonetheless, different difficulties are as yet present in the trust the board framework for observing and assessing the QoS. This paper talks about the current obstructions present in the trust framework. The objective of this paper is to audit the available trust models. The issues like insufficient trust between the supplier and client have made issues in information sharing likewise tended to here. Besides, it lays the limits and their enhancements to help specialists who mean to investigate this point.

PNTRS

A news recommendation system not only must recommend the latest, trending and personalized news to the users but also give opportunity to know about the people’s opinion on trending news. Most of the existing news recommendation systems focus on recommending news articles based on user-specific tweets. In contrast to these recommendation systems, the proposed Personalized News and Tweet Recommendation System (PNTRS) recommends tweets based on the recommended article. It firstly generates news recommendation based on user’s interest and twitter profile using the Multinomial Naïve Bayes (MNB) classifier. Further, the system uses these recommended articles to recommend various trending tweets using fuzzy inference system. Additionally, feedback-based learning is applied to improve the efficiency of the proposed recommendation system. The user feedback rating is taken to evaluate the satisfaction level and it is 7.9 on the scale of 10.

A Collaborative Ranking Approach for Discovery and Selection of Cloud Services

Cloud computing is getting more popular due to its extraordinary features such as on-demand availability of computing resources and software services. A variety of services have been deployed to offer analogous functionalities. However, the difficulty to identify reliable services has fascinated the attention of researchers. Thus, the trust and reputation concept have been introduced to evaluate the trustworthiness of services over cloud. Most of the existing research works fully trust on service user's feedback rating for ranking cloud services, which may often lead to biasness towards positive and negative feedback rating. To avoid aforementioned issues, this chapter proposes a novel approach to evaluate cloud service reputation along with cloud service reputation evaluation model to discover reliable cloud services. Experimental result shows that proposed approach provides effective solution for prediction of cloud service reputation, which can be helpful in performing reliable service discovery and selection over cloud.

MANAGEMENT OF LABOR POTENTIAL OF SELF-REGULATORY ORGANIZATIONS

The article is devoted to the problems of managing labor potential of self-regulatory organizations. The author structures the social factors that influence the labor potential of the staff; some measures are proposed that could stimulate the implementation of self-regulatory organizations when creating optimal conditions in the building of management systems of labor potential. The author proves the need for a single information resource, which is an information platform for the placement of monitoring the activities of all registered self-regulatory organizations, and by allowing on-line tools to generate a feedback rating system and scales of assessment of their activities.

Modeling for Reputation Computing Research Base on C2C Communities

Trust is part of the main problems in the development of C2C e-commerce. Calculating the value of reputation based on feedback rating is an effective way to create trust in e-commerce transactions. This paper proposes a computing model built on the reputation of e-commerce by introducing a feedback score, the transaction value, time, penalty factor and other parameters. Simulation results demonstrate that the model can effectively prevent the credibility of slander, reputation hype, reputation conspiracy and other issues.

The Impact of Reputation Timing and Source on Auction Outcomes

This paper uses data from electric guitar auctions on eBay to further examine the impact of reputation on the likelihood that an auction ends in a sale. It extends the existing literature by examining both the impact of the overall eBay feedback rating as well as feedback from shorter time periods. The results of this paper suggest that recent feedback, and in particular recent negative feedback, is of particular importance in explaining the likelihood that an auctioned item sells. Other feedback related factors included in this paper are measures for the source of feedback (i.e. buying or selling behavior) and whether negative feedback is product or seller related.