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Constructing a Context-Aware Service-Oriented Reputation Model Using Attention Allocation Points
Abstract
In this paper we examine the problem of rich information environments and the need to narrow the agents attention to what is important for them to interact and later to evaluate and transfer reputation values, using attention allocation technique (AA). We also argue that this cannot be done without the aid of service oriented architecture (SOA). Reputation is used in our work as a service, presenting a new concept- that is reputation-as-a-service (RaaS). We then present a service-oriented model for optimizing the presentation and the use of reputation in order to maximize its value to both users and providers.
... Semantic Web technologies were developed with the goal to provide common data representation framework in order to facilitate the integration of multiple sources to draw new conclusions, increasing the utility of information by connecting it to its definitions and to its context, more efficient information access and analysis [7]. Thus, we use some of these technologies to develop the proposed reputation model, based on our previous analysis of the model requirements.[3][5] This paper starts with a brief introduction to the existing approaches in reputation systems and discusses the issues raised from using a single reputation value. ...
... sum, average, deterministic, bayesian, fuzzy systems, etc.), different ways of data entry or enquiry that result in different representations, interaction styles and trust rating scales. In [3] we analyzed the rating systems of some known communities and showed how they have different rating scales, visual representations, and entities to be evaluated. ...
... In this section we give a general description of the model and its benefits abstracted/detached from the semantic technologies used. In our previous work [4][5][3] we analyzed some of the aforementioned problems by focusing on reputation misrepresentation and presented a data model where the representation of an entity's reputation is replaced by a reputation object instead of a single value. In this paper, we present the formal model as well as its development details. ...
Reputation is a complex concept that has a major role in fields like social sciences, economics as well as computer science. Representing it as a simple form of property-rating or a vector of ratings strips it from its original notion and postulation. It does not also facilitate the derivation of meaningful conclusions from it. This paper presents a semantic model for the representation of reputation as a complex object - a so called Reputation Object (RO). We also argue that using ontologies, and other semantic web technologies, to represent the reputation object model is essential to achieve reputation interoperability and portability between different domains. The contribution is a semantic design artifact for reputation representation that agrees with the theoretical and social formation and processing of reputation information. We also show some applications and how this ontology-based reputation model can be applied in a rule-based open reputation system. The work presented here has significant implications for e-market studies of knowledge sharing.
... The range of possible values for a trust level and the meaning of these values varies according to each system. [3] E-markets use reputation to manage trust between service providers and consumers. In this domain, users collaboration is essential i.e. ...
... Examples of the work done in this area can be found in [16][18] [17] and more. In [7], we explain the steps to construct a reputation system and elaborate on their types in [5][9] [3]. ...
Reputation systems aim to provide a mechanism for establishing trust for online interactions attempting to mimic their real-world counterparts. Reputation-based approaches depend on the users local experiences and feedback to create a soft measure for trust decision. They use various clues and past experience to decide on taking the risk of dealing with an entity. Reputation communities cannot exchange reputation or reputation information following an isolated-silos approach. The reasons for this varies from missing contexts in the reputation representations and heterogeneity in these representations, to technical reasons such as not being represented in an interoperable knowledge representation method. Developing interoperable reputation ontologies requires a technology that can provide means of integrating data sources and methods to relate the data to its explicit semantics. In this paper, we describe our design decisions in developing our reputation object (RO) ontology using semantic web technologies. The main motivation that leads these decision is to facilitate reputation information exchange or reputation interoperability along with model expressivity. Therefore, choosing the ontology language and specific APIs is explained in relation to this motivation.
... • different representation for this value i.e. different interactions styles, scales, etc.. [1] • difficulty of collecting evidence ...
... As discussed earlier, one of the major problems in trust management systems is the correct representation of reputation. In our previous work [3], [1], [2] we have analyzed the problem and proposed a new way of representing reputation by the means of what we call Reputation Object (RO), along with setting requirements for solving this problem. The basic idea and solution is that reputation cannot be viewed as a single value anymore. ...
This paper discusses the meaning and the role of Trust and Reputation in Internet-of-Service and e-Commerce environments following a comparative case study. Both environments represent paradigms through which the Internet is seen as a huge infrastructure where electronic services or real products are traded on. In comparison to electronic commerce, participating in an Internet-of-Services can be full of risks for all participants. Even well known security mechanisms are not able to close all gaps of access and usage control. This paper discusses the concepts of trust and reputation and brings to light the relation between these concepts to security mechanisms, Service-Level-Agreements, and quality measurements in order to enable Usage Control. The proposed solution is based on our previous model of reputation objects. The discussion also introduces a new concept of what we call reputation auditing where quality processes are considered part of reputation management not the other way around.
... After matching user requirements and provider capabilities, we use the reputation of the providers to produce the final list of potential providers to host parts of the user's data. A provider's reputation holds the details of the historical performance plus the ratings in the service registries and is saved in a Reputation Object (introduced in our previous work [3], [2], [4]). By reading this object, we know a provider's reputation concerning each performance parameter (e.g. has high response time, low price). ...
... After matching user requirements and provider capabilities, we use the reputation of the providers to produce the final list of potential providers to host parts of the user's data. A provider's reputation holds the details of the historical performance plus the ratings in the service registries and is saved in a Reputation Object (introduced in our previous work [3], [2], [4]). By reading this object, we know a provider's reputation concerning each performance parameter (e.g. has high response time, low price). ...
... In the social trust network, reviews and ratings from a user are consistently found to be valuable by his trustees. Furthermore, products online can also be regarded as services, and several researches on services recommendation have utilized the datasets from Epinions (Alnemr, Bross, & Meinel, 2009;Noor & Sheng, 2014). Thus, Epinions is an ideal source for our experiments. ...
Given the increasing applications of service computing and cloud computing, a large number of Web services are deployed on the Internet, triggering the research of Web service recommendation. Despite of service QoS, the use of user feedback is becoming the current trend in service recommendation. Likewise in traditional recommender systems, sparsity, cold-start and trustworthiness are major issues challenging service recommendation in adopting similarity-based approaches. Meanwhile, with the prevalence of social networks, nowadays people become active in interacting with various computers and users, resulting in a huge volume of data available, such as service information, user-service ratings, interaction logs, and user relationships. Therefore, how to incorporate the trust relationship in social networks with user feedback for service recommendation motivates this work. In this paper, we propose a social network-based service recommendation method with trust enhancement known as RelevantTrustWalker. First, a matrix factorization method is utilized to assess the degree of trust between users in social network. Next, an extended random walk algorithm is proposed to obtain recommendation results. To evaluate the accuracy of the algorithm, experiments on a real-world dataset are conducted and experimental results indicate that the quality of the recommendation and the speed of the method are improved compared with existing algorithms.
... The implementation of the ontology is described in section III-D. This ontology was used to represent an entity's reputation in several domains such as multi-agent based system (in [16], as the reputation of an agent and a way for decision making), for usage control in Internet-of-services (IoS) [4], and as an underlying ontology for a SOA reputation service in [3] that was later used in [25] for cloud service provider selection. It was designed mainly to facilitate reputation information exchange or reputation interoperability in any domain. ...
Reputation has been explored in diverse disciplines such as artificial intelligence, electronic commerce, peer-to-peer network, and multi-agent systems. Recently it has been a vital component for ensuring trust in web services and service oriented architecture domains. In this paper, we show details about our context-aware reputation framework. The framework is based on our semantic representation model for reputation called Reputation Object (RO) model. We discuss the advantages and propositions to construct such framework, its components, and how it is implemented. The importance of developing and using such generic reputation framework is highlighted within the emergence of the Semantic Web and service oriented architecture.
... They will have to perform a scrutiny on the security capabilities of the service provider independently. This has to include: studying particular security policies and service level agreements (SLA) that are usually written in a plain natural language 1 and inspecting the facilities of the service provider. Carrying on these two tasks is indeed inefficient as well as time consuming. ...
Cloud Computing as a service on demand architecture has become a topic of interest in the last few years. The outsourcing of duties and infrastructure to external parties enables new services to be established quickly and with low financial risk. These services also can be scaled on demand. Nevertheless, several issues such as security and legality should be considered before entering the cloud. The financial benefits of cloud services conflict with the need to secure and control the access to outsourced information. Companies have to comply with diverse laws across jurisdictions and are accountable to various national regulators. Security requirements may not be compatible with those offered by existing providers. In this paper, we propose an architecture to facilitate the integration of these security requirements in the cloud environment and to address the legal issues attached. Our approach customizes the selection of a service provider based on the companies preference. We also define a trusted third party to handle the monitoring and auditing processes over different service providers.
... It has also the possibility to define a comparison and ordering function; OrderFunction to compare between values within each criterion. The ontology is implemented using Protégé-OWL and also a Java library is implemented to facilitate the integration within any system [4] [2]. It has been used with several use cases. ...
Web users while collaborating over social networks and micro-blogging services also contribute to news coverage worldwide. News feeds come from mainstream media as well as from social networks. Often feeds from social networks are more up-to-date and, for user's view, more credible than those that come from mainstream media. But the overwhelming amount of information requires to personally filter through it until one gets what is really needed. In this paper, we describe our idea of a personalized news network built on current Web technologies and our research projects by filtering Twitter and Facebook messages using both trend mining and reputation approaches. Based on the example of Egyptian revolution, we explain the main idea of personalized news.
... eBay 2) Opinions and activity sharing sites e. Table I shows the rating methods and rating levels from a study we conducted on a several reputation systems. [3] Each System use different kind of rating/raking to evaluate an entity's reputation. In online reputation communities, trust and reputation (or rating at this point) is represented numerically or graphically using bars and stars, karma, or in natural language (i.e. ...
For several years online reputation systems have been evolving in an attempt to mimic their real-world counterparts. Rating in online communities comes in many forms such as numbers, stars, scales, etc.. The underlying aggregation or computation methods varies according to the community's information sources and perception of reputation. However, the notion of reputation is a complex one that represented as a simple form of property-rating or a vector of ratings, strips it from its original concept and postulation. It does not also facilitate the derivation of meaningful conclusions from it. In this paper, we present studies we designed to examine how users perceive reputation as well as what reputation information being used and whether rating is enough to convey an entity's reputation. These studies are analyzed and discussed based on the results. Moreover, we show how our reputation ontology - that is designed to facilitate reputation knowledge transfer on the communication level- is used in a simple interface of multiple ratings. The model is based on semantic web technologies.
... The implementation for processing an RO was developed using Jena-API 11 . This ontology was used to represent an entity's reputation in several domains Fig. 7. Reputation Object Ontology [5] such as multi-agent based system (in [25], as the reputation of an agent and a way for decision making), for usage control in Internet-of-services (IoS) [4], and as an underlying ontology for a SOA reputation service in [3] that was later used in [34] for cloud service provider selection. ...
Reputation has been explored in diverse disciplines such as artificial intelligence, electronic commerce, peer-to-peer network,
and multi-agent systems. Recently it has been a vital component for ensuring trust in web services and service oriented architectures
domains. Although there are several studies on reputation systems as well as reputation models, there is no study that covers
reputation ontologies especially the ones implemented using standardized frameworks like semantic technologies. In this paper,
we show the evolution towards reputation ontologies and investigate existing ones in the domains of multi-agent systems, web
services, and online markets. We define the requirements for developing a reputation ontology and use them to analyze some
of the existing ontologies. The components and functionalities of reputation models and systems are described briefly and
the importance of developing and using reputation ontologies is highlighted within the emergence of the Semantic Web and Semantic
Web services.
... After matching user requirements and provider capabilities, we use the reputation of the providers to produce the final list of potential providers to host parts of users data. A provider's reputation holds the details of his historical performance plus his ratings in the service registries and saved in a Reputation Object (introduced in our work in [4], [3], [2]). Simply, the object holds a profile of the behavior or performance of the provider in several contexts. ...
Cloud Computing as a service on demand architecture has become a topic of interest in the last few years. The outsourcing of duties and infrastructure to external parties enables new services to be established quickly, scaled on demand, and with low financial risk. Cloud storage enables organizations to manage their data with low operational expenses. Nevertheless, several issues such as security and the risk to become dependent on a provider for its service should be considered before entering the cloud. In general, a switch of a storage provider is associated with high costs of adapting new APIs and additional charges for inbound and outbound bandwidth and requests. In this paper we use the principle of RAID-technology in cloud infrastructure to manage data distribution across cloud storage providers. The distribution is based on users expectations regarding providers geographic location, quality of service, providers reputation, and budget preferences. Our approach allows users to avoid vendor lock-in, reduce cost of switching providers and increase security and availability of their data. We also explain on how the proposed system removes the complexity of interacting with multiple storage providers while maintaining security.
... Luckily, some schema matching algorithms, such as Similarity Flooding, which we used, also return metrics on the quality of the mapping achieved. Publishing these quality attributes along with the mapping will lead to increased transparency for data on the Web and can be used in the context of data provenance tracking [6] and trust management [1] . Since we intend our work being valuable for a variety of use cases, and also not be tied to specific programming languages, the second direction of research will be to evaluate practictal implementations of our approach with different programming languages and also with different schema matching algorithms, in order to provide maximum support for a large number of software de- velopers. ...
This paper presents a new method for publishing and consuming RDF data using object-oriented programming. We improve Object Triple Mapping (OTM) by separating (1) the transformation process between object-oriented data and RDF data from (2) explaining the transformation results using established Semantic Web vocabulary. To achieve this separation, we introduce a canonical vocabulary for object models. As a result, the Semantic Web expertise required to develop RDF-enabled applications is reduced.
Reputation plays an important role for users in choosing or paying for multimedia applications or services. Some efficient multimedia reputation-measurement approaches have been proposed to achieve accurate reputation measurement based on feedback ratings that users give to a multimedia service after invoking. However, the implementation of these approaches suffers from the problems of wide abuse and low utilization of user context. In this article, we study the relationship between user context and feedback ratings according to which one user often gives different feedback ratings to the same multimedia service in different user contexts. We further propose an enhanced user context-aware reputation-measurement approach for multimedia services that is accurate in two senses: (1) Each multimedia service has three reputation values with three different user context levels when its feedback ratings are sufficient and (2) the reputation of a multimedia service with different user context levels is found using user context sensitivity and user similarity when its feedback ratings are limited or not available. Experimental results based on a real-world dataset show that our approach outperforms other approaches in terms of accuracy.
This chapter focuses on the discussion about how the data collected by the crawler (refer to Chap. 11) can and should be analyzed to extract, exploit and represent meaningful knowledge and to leverage content- and context-related structures and dynamics of partial blogospheres. There is a multitude of data analyzers that could process the information as collected by the crawler (refer to Extraction in Fig. 10. 1). Our research supports the overall subdivision of this multitude into two general categories, namely content analyses and network analyses (refer to Analysis in Fig. 10. 1).
Cloud Computing as a service-on-demand architecture has grown in importance over the previous few years. One driving force of its growth is the ever increasing amount of data which is supposed to outpace the growth of storage capacity. This way, public cloud storage services enable organizations to manage their data with low operational expenses. However, the benefits of cloud computing come along with challenges and open issues such as security, reliability and the risk to become dependent on a provider for its service. In general, a switch of a storage provider is associated with high costs of adapting new APIs and additional charges for inbound and outbound bandwidth and requests. In this paper, we describe the design, architecture and implementation of Cloud-RAID, a system that improves availability, confidentiality and integrity of data stored in the cloud. To achieve this objective, we encrypt user's data and make use of the RAID-technology principle to manage data distribution across cloud storage providers. Our approach allows users to avoid vendor lock-in, and reduce significantly the cost of switching providers. In general, the data distribution is based on users' expectations regarding providers geographic location, quality of service, providers reputation, and budget preferences. In this paper, we also discuss the security functionality and reveal our observations on the overall performance when encrypting and encoding user's data.
One of the critical success factors of event-driven systems is the capability of detecting complex events from simple and ordinary event notifications. Complex events which trigger or terminate actionable situations can be inferred from large event clouds or event streams based on their event instance sequence, their syntax and semantics. Using semantics of event algebra patterns defined on top of event instance sequences for event detection is one of the promising approaches for detection of complex events. The developments and successes in building standards and tools for semantic technologies such as declarative rules and ontologies are opening novel research and application areas in event processing. One of these promising application areas is semantic event processing. In this paper we contribute with a conceptual approach which supports the implementation of the vision of semantic event-driven systems; using Semantic Web technologies, benefiting from complex event processing, and ensuring quality through trust and reputation management. All of these novel technologies leads to more intelligent decision supporting systems.
Many online services require some form of trust between users – trust that a seller will deliver goods as advertised, trust that an author's thoughts are worth the time spent on reading them. To accommodate an internet community where users are constantly interacting with strangers, online services often construct proprietary reputation management systems for their community, with the side effect of locking users into that service if they wish to maintain their reputation. In contrast, this paper outlines EgoSphere, a system for portable Internet reputations, so that reputations built on one service can be used elsewhere. EgoSphere hinges on the use of correlational statistics to automatically project reputations from one service to other similar services. To achieve these goals, EgoSphere must gather webservices' reputation data. EgoSphere avoids the unreasonable expectation that all webservices will publish their reputation databases, while also avoiding the use of a webcrawling robot (a violation of many webservices' robots.txt restrictions and source of incurring additional website load) by gathering its reputation data using a distributed passive robot system. This system simulates the function of a standard web-crawling robot by using webproxies on users' computers to analyze the responses to standard webservice requests. This paper outlines the design and proof-of-concept implementation of EgoSphere, targeted specifically at providing portable reputations for bulletin-board style internet services.
Reputation systems are typically based on ratings given by the users. When there are no mechanisms in place to detect collusion and deception, combining user testimonies as such to form a provider's reputation may not give an accurate assessment, especially if the context of the ratings is not known. Moreover, such systems are vulnerable to manipulations by malicious users. Hence it becomes essential to establish the validity of the ratings prior to using them in formulating reputation based on such ratings. It is important to identify the rationale behind the ratings so that similar ratings (or ratings pertaining to a context) can be aggregated to obtain a reputation value meaningful in that context. We propose a fuzzy approach to analyze user rating behavior to infer the rationale for ratings in a web services environment. This inference of rationale facilitates the system to validate ratings, detect deception and collusion, identify user preferences and provide recommendations to users.
The duality of expert finding and query answering is characterized. Expert querying and redirection are realized in the Rule Responder platform. The use case of the RuleML-2007 organization is discussed. La dualité de la réponse aux requêtes et de la recherche d'experts est caractérisée. Les requêtes de recherche d'experts et les redirections sont réalisées dans la plate-forme Rule Responder. Le cas d'utilisation de l'organisation RuleML-2007 est traité.
The members of electronic communities are often unrelated to each other; they may have never met and have no information on each other's reputation. This kind of information is vital in electronic commerce interactions, where the potential counterpart's reputation can be a significant factor in the negotiation strategy. Two complementary reputation mechanisms are investigated which rely on collaborative rating and personalized evaluation of the various ratings assigned to each user. While these reputation mechanisms are developed in the context of electronic commerce, it is believed that they may have applicability in other types of electronic communities such as chatrooms, newsgroups, mailing lists, etc.
Regulators, industry groups, consultants, and individual companies have developed elaborate guidelines over the years for assessing and managing risks in a wide range of areas, from commodity prices to natural disasters. Yet they have all but ignored reputational risk, mostly because they aren't sure how to define or measure it. That's a big problem, say the authors. Because so much market value comes from hard-to-assess intangible assets like brand equity and intellectual capital, organizations are especially vulnerable to anything that damages their reputations. Moreover, companies with strong positive reputations attract better talent and are perceived as providing more value in their products and services, which often allows them to charge a premium. Their customers are more loyal and buy broader ranges of products and services. Since the market believes that such companies will deliver sustained earnings and future growth, they have higher price-earnings multiples and market values and lower costs of capital. Most companies, however, do an inadequate job of managing their reputations in general and the risks to their reputations in particular. They tend to focus their energies on handling the threats to their reputations that have already surfaced. That is not risk management; it is crisis management--a reactive approach aimed at limiting the damage. The authors provide a framework for actively managing reputational risk. They introduce three factors (the reputation-reality gap, changing beliefs and expectations, and weak internal coordination) that affect the level of such risks and then explore several ways to sufficiently quantify and control those factors. The process outlined in this article will help managers do a better job of assessing existing and potential threats to their companies' reputations and deciding whether to accept a particular risk or take actions to avoid or mitigate it.
An important characteristic of journals is how influential they are in the generation and dissemination of scholarly knowledge in a discipline. We report a citation analysis of 49 marketing and marketing-related journals to assess their relative influence based on the index of structural influence proposed by Salancik (1986). We investigate the level and span of influence of the 49 journals, both in the marketing discipline as a whole and in five specific sub-areas of marketing. As expected, the Journal of Marketing emerges as the most influential journal in the discipline and as the journal with the broadest span of influence across all sub-areas of marketing. However, different journals are most influential in each of the sub-areas, and the Journal of Marketing is particularly influential among the applied marketing journals. We also find that the index of structural influence is significantly correlated with all other measures of influence but least so with the impact factors reported in the Social Sciences Citation Index.
After entering the realm of computing over a decade ago, the term trust management has evolved to encompass many concepts and mechanisms that bring it closer to its intuitive interpretation. This chapter will outline the evolution and present the catalyst(s) for each phase in its metamorphosis. In each stage, trust management tools were constructed to showcase the current understanding in the field. These tools will be discussed and their strengths, domains of application, and scope for improvement presented. The foundation of trust management technology can be found in security notions, for example credentials, in mathematical computation and in formal (and informal) reputation models. Each of these categories and their hybrids will be highlighted. This chapter should leave the reader with (1) a holistic view of the trust management problem, (2) a clear differentiation of trust management from other fields (and terms) in the computer security arena, and (3) knowledge of the appropriate domain of usage for each system.
After entering the realm of computing over a decade ago, the term trust management has evolved to encompass many concepts and mechanisms that bring it closer to its intuitive interpretation. This chapter will outline the evolution and present the catalyst(s) for each phase in its metamorphosis. In each stage, trust management tools were constructed to showcase the current understanding in the field. These tools will be discussed and their strengths, domains of application, and scope for improvement presented. The foundation of trust management technology can be found in security notions, for example credentials, in mathematical computation and in formal (and informal) reputation models. Each of these categories and their hybrids will be highlighted. This chapter should leave the reader with (1) a holistic view of the trust management problem, (2) a clear differentiation of trust management from other fields (and terms) in the computer security arena, and (3) knowledge of the appropriate domain of usage for each system.
Online reputation systems have become important tools for supporting commercial as well as noncommercial online interactions. But as online users become more and more reliant on these systems, the question of whether the operators of online reputation systems may be legally liable for problems with these systems becomes both interesting and important. Indeed, lawsuits against the operators of online reputation systems have already emerged in the United States regarding errors in the information provided by such systems. In this chapter, we will take the example of eBay's Feedback Forum to review the potential legal liabilities facing the operators of online reputation systems. In particular, the applicability of the Canadian law of negligent misrepresentation and of defamation will be covered. Similar issues may be expected to arise in the other common law jurisdictions.
A host of recent studies show that attention allocation has important economic consequences. This paper reports the first empirical test of a cost-benefit model of the endogenous allocation of attention. The model assumes that economic agents have finite mental processing speeds and cannot analyze all of the elements in complex problems. The model makes tractable predictions about attention allocation, despite the high level of complexity in our environment. The model successfully predicts the key empirical regularities of attention allocation measured in a choice experiment. In the experiment, decision time is a scarce resource and attention allocation is continuously measured using Mouselab. Subject choices correspond well to the quantitative predictions of the model, which are derived from cost-benefit and option-value principles.
Reputation is a crucial factor in trust and thus in Web communities. Trust strategies may involve investigating user reputation or directly using transitive reputation to form the Web of Trust. We suggest an approach that takes advantage of both strategies without increasing the cost of investigation. Several systems nowadays form what we call ldquouser Web communitiesrdquo. In these communities, reputation related to different contexts needs to be exchanged. The perception, calculation and interpretation of this reputation differ from one community to another. We propose the development of reference models to diminish the distance between these multi-perceptions. We also propose the use of reputation centers to facilitate reputation transfer and highlight the importance of their role in analyzing attacks on reputation.
Getting more from Reputation Systems:A Context–aware Reputation
- Alnemr
- Rehab
Alnemr, Rehab, and Christoph Meinel. "Getting more from Reputation Systems:A Context–aware Reputation
Taking Trust Management to the Next Level In Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies and Applications
- Rehab Alnemr
- Matthias Quasthoff