10,263 research outputs found

    Context-dependent Trust Decisions with Subjective Logic

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    A decision procedure implemented over a computational trust mechanism aims to allow for decisions to be made regarding whether some entity or information should be trusted. As recognised in the literature, trust is contextual, and we describe how such a context often translates into a confidence level which should be used to modify an underlying trust value. J{\o}sang's Subjective Logic has long been used in the trust domain, and we show that its operators are insufficient to address this problem. We therefore provide a decision-making approach about trust which also considers the notion of confidence (based on context) through the introduction of a new operator. In particular, we introduce general requirements that must be respected when combining trustworthiness and confidence degree, and demonstrate the soundness of our new operator with respect to these properties.Comment: 19 pages, 4 figures, technical report of the University of Aberdeen (preprint version

    An efficient and versatile approach to trust and reputation using hierarchical Bayesian modelling

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    In many dynamic open systems, autonomous agents must interact with one another to achieve their goals. Such agents may be self-interested and, when trusted to perform an action, may betray that trust by not performing the action as required. Due to the scale and dynamism of these systems, agents will often need to interact with other agents with which they have little or no past experience. Each agent must therefore be capable of assessing and identifying reliable interaction partners, even if it has no personal experience with them. To this end, we present HABIT, a Hierarchical And Bayesian Inferred Trust model for assessing how much an agent should trust its peers based on direct and third party information. This model is robust in environments in which third party information is malicious, noisy, or otherwise inaccurate. Although existing approaches claim to achieve this, most rely on heuristics with little theoretical foundation. In contrast, HABIT is based exclusively on principled statistical techniques: it can cope with multiple discrete or continuous aspects of trustee behaviour; it does not restrict agents to using a single shared representation of behaviour; it can improve assessment by using any observed correlation between the behaviour of similar trustees or information sources; and it provides a pragmatic solution to the whitewasher problem (in which unreliable agents assume a new identity to avoid bad reputation). In this paper, we describe the theoretical aspects of HABIT, and present experimental results that demonstrate its ability to predict agent behaviour in both a simulated environment, and one based on data from a real-world webserver domain. In particular, these experiments show that HABIT can predict trustee performance based on multiple representations of behaviour, and is up to twice as accurate as BLADE, an existing state-of-the-art trust model that is both statistically principled and has been previously shown to outperform a number of other probabilistic trust models

    The availability of land for perennial energy crops in Great Britain

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    This paper defines the potentially available land for perennial energy crops across Great Britain as the first component of a broader appraisal undertaken by the ā€˜Spatial Modelling of Bioenergy in Great Britain to 2050ā€™ project. Combining data on seven primary constraints in a GIS reduced the available area to just over 9 M ha (40% of GB). Adding other restrictions based on land cover naturalness scores to represent landscape considerations resulted in a final area of 8.5 M ha (37% of GB). This distribution was compared with the locations of Miscanthus and SRC willow established under the English Energy Crop Scheme during 2001ā€“2011 and it was found that 83% of the planting fell within the defined available land. Such a correspondence provides confidence that the factors considered in the analysis were broadly consistent with previous planting decisions

    Trust Management within Virtual Communities: Adaptive and Socially-Compliant Trust Model

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    21 pagesRecent years have witnessed increasing interest of people in sharing, collaborating and interacting in many different ways among new social structures called Virtual Communities (VC). They represent aggrega- tions of entities with common interests, goals, practices or values. VCs are particularly complex environments wherein trust became, rapidly, a prerequisite for the decision-making process, and where traditional trust establishment techniques are regularly challenged. In our work we are considering how individual and collective trust policies can be managed, adapted and combined. To this aim, we propose an Adaptive and Socially-Compliant Trust Management System (ASC-TMS) based on multi-agent technologies. In this framework, policies are used as concrete implementations of trust models in order to specify both (i) user-centred (i.e. personal) and community-centred (i.e. collective) trust requirements. Agents are used to manage and combine these different policies in a decentralized and flexible way. We describe the functionalities and the architecture that supports them and discuss also a prototype implementation

    An adaptive technique for content-based image retrieval

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    We discuss an adaptive approach towards Content-Based Image Retrieval. It is based on the Ostensive Model of developing information needsā€”a special kind of relevance feedback model that learns from implicit user feedback and adds a temporal notion to relevance. The ostensive approach supports content-assisted browsing through visualising the interaction by adding user-selected images to a browsing path, which ends with a set of system recommendations. The suggestions are based on an adaptive query learning scheme, in which the query is learnt from previously selected images. Our approach is an adaptation of the original Ostensive Model based on textual features only, to include content-based features to characterise images. In the proposed scheme textual and colour features are combined using the Dempster-Shafer theory of evidence combination. Results from a user-centred, work-task oriented evaluation show that the ostensive interface is preferred over a traditional interface with manual query facilities. This is due to its ability to adapt to the user's need, its intuitiveness and the fluid way in which it operates. Studying and comparing the nature of the underlying information need, it emerges that our approach elicits changes in the user's need based on the interaction, and is successful in adapting the retrieval to match the changes. In addition, a preliminary study of the retrieval performance of the ostensive relevance feedback scheme shows that it can outperform a standard relevance feedback strategy in terms of image recall in category search

    Paradigms, poverty and adaptive pluralism

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    In earlier analysis, two paradigms were identified in development professionalism, thinking and practice: one, often dominant, associated with things; and one, often subordinate, associated with people. Current development thinking and practice have diverged into two clusters, with procedures associated with the paradigm of things imposed by powerful actors and organisations in tension and contradiction with participatory methodologies (PMs) associated with the paradigm of people. A binocular vision sees both. This sets out to see further, and whether participatory methodologies (PMs) can bridge these binaries with both ā€“ and complementarities and win-wins. In recent years, PMs have proliferated. Contributing factors have been the way methods have multiplied, their versatility, adaptability and combinability, the explosion of applications of Information and Communication Technologies and Web 2.0, and more speculatively an increase in the number of people working in a creative participatory way. PMs that combine methods have proved increasingly versatile and adaptable to contexts and purposes. PMs are well suited to understanding and expressing the local, complex, diverse, dynamic, uncontrollable and unpredictable (lcdduu) realities experienced by many poor people. These contrast with the controlled conditions and universalities sought in much high status professionalism. Paradigmatically and practically, four domains have increasingly converged and cohere: PMs; poor peopleā€™s lcdduu realities; technology; and complexity. Paradigm can then be defined as a coherent and mutually supporting pattern of: concepts and ontological assumptions; values and principles; methods, procedures and processes; roles and behaviours; relationships; and mindsets, orientations and predispositions. Empirically, a paradigm of adaptive and participatory pluralism can be inferred from experience and examples. This fits with the realities of poor people as adaptive agents and with PMs seen through lenses of technology and complexity. It contrasts with a paradigm of neo- Newtonian practice. Adaptive pluralism embraces, underpins and expresses ideas and practices of reflexivity, continuous learning, value and principle-based eclectic improvisation, co-evolution and continuous emergence. Conceptually, it embodies paradigmatic synergies. Practically, it offers win-win solutions and generates an agenda for action

    Web and Semantic Web Query Languages

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    A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion

    Recommender Systems

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    The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has a great scientific depth and combines diverse research fields which makes it of interests for physicists as well as interdisciplinary researchers.Comment: 97 pages, 20 figures (To appear in Physics Reports

    Skill Spanning in the Online Labor Market: A Double-Edged Sword?

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    Freelancers in online labor markets often display many skills in their profiles to increase their chances of being hired. However, such behavior may lead to the skills they display straddling multiple categories, that is, ā€œskill spanning.ā€ In this paper, we extend the concept of category spanning into online labor markets in the form of skill spanning and empirically examine (1) how freelancersā€™ skill spanning affects employersā€™ hiring decisions for two different types of jobs (low- and high-skill jobs, respectively), and (2) how freelancersā€™ skill matching moderates the effects of skill spanning on employersā€™ hiring decisions. Based on a unique dataset of 12,428 high-skill jobs and 19,875 low-skill jobs on a leading online labor platform, we find that freelancersā€™ skill spanning has different impacts on employersā€™ hiring decisions for these two job types. Specifically, for high-skill jobs, freelancersā€™ skill spanning reduces their likelihood of winning contracts; however, for low-skill jobs, freelancersā€™ skill spanning and their probabilities of winning contracts demonstrate an inverse U-shape relationship. Furthermore, freelancersā€™ skill matching can moderate the negative effects of skill spanning for high-skill jobs but not for low-skill jobs. Our findings provide guidelines for different stakeholders in online labor markets, including freelancers and platform owners
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