The realization that scholarly publications are discussed and have influence on discourse outside scientific and academic domains has given rise to area of scientometrics called alternative metrics ...or "altmetrics". Furthermore, researchers in this field tend to focus primarily on measuring scientific activity on social media platforms such as Twitter, however these count-based metrics are vulnerable to gaming because they tend to lack concrete justification or reference to the primary source. In this collaboration with Elsevier, we extend the conventional citation graph to a heterogeneous graph of publications, scientists, venues, organizations and more authoritative media sources such as mainstream news and weblogs. Our approach consists of two parts: one is integrating the bibliometric data with the social data such as blogs, mainstream news. The other involves understanding how standard graph-based metrics can be used to predict the academic impact. Our result showed the computed graph-based metrics can reasonably predict the academic impact of early stage researchers.
Real-world sequential decision-making tasks are usually complex, and require trade-offs between multiple–often conflicting–objectives. However, the majority of research in reinforcement learning (RL) ...and decision-theoretic planning assumes a single objective, or that multiple objectives can be handled via a predefined weighted sum over the objectives. Such approaches may oversimplify the underlying problem, and produce suboptimal results. This extended abstract outlines the limitations of using a semi-blind iterative process to solve multi-objective decision making problems. Our extended paper 4, serves as a guide for the application of explicitly multi-objective methods to difficult problems.
This paper describes the development of a networked music application at Trinity College Dublin. Smart radio is a web-based application, which uses streaming audio technology and collaborative ...recommendation techniques to allow listeners build, manage and share music programmes. While it is generally acknowledged that music distribution over the web will dramatically change how the music industry operates, there are few prototypes available to demonstrate how this could work in a managed way. The smart radio approach is to have people manage their music resources by putting together personalised music programmes. These programmes can then be swapped using techniques of collaborative recommendation to find similarities between users. The smart radio system currently runs within the computer science intranet with permission from the Irish music rights organisation (IMRO). It is a prototype system for an ‘always on’ high bandwidth Internet connection such as asymmetric digital subscriber lines (ADSL).
RDF4Led Le-Tuan, Anh; Hayes, Conor; Wylot, Marcin ...
Proceedings of the 8th International Conference on the Internet of Things,
10/2018
Conference Proceeding
Semantic interoperability for the Internet of Things(IoT) is being enabled by standards and technologies from the Semantic Web. As recent research suggests a move towards decentralised IoT ...architectures, our focus is on how to enable scalable and robust RDF engines that can be embedded throughout the architecture, in particular at edge nodes. RDF processing at edge enables the creation of semantic integration gateways for locally connected low-level devices. We introduce a lightweight RDF engine, which comprises of RDF storage and SPARQL processor, for the lightweight edge devices, called RDF4Led. RDF4Led follows the RISCstyle (Reduce Instruction Set Computer) design philosophy. The design comprises a flash-aware storage structure, an indexing scheme and a low-memory-footprint join algorithm which improves scalability as well as robustness over competing solutions. With a significantly smaller memory footprint, we show that RDF4Led can handle 2 to 5 times more data than RDF engines such as Jena TDB and Virtuoso. On three types of ARM boards, RDF4Led requires 10--30% memory of its competitors to operate up to 30 million triples dataset; it can perform faster updates and can scale better than Jena TDB and Virtuoso. Furthermore, we demonstrate considerably faster query operations than Jena TDB.
The recent paper `"Reward is Enough" by Silver, Singh, Precup and Sutton posits that the concept of reward maximisation is sufficient to underpin all intelligence, both natural and artificial. We ...contest the underlying assumption of Silver et al. that such reward can be scalar-valued. In this paper we explain why scalar rewards are insufficient to account for some aspects of both biological and computational intelligence, and argue in favour of explicitly multi-objective models of reward maximisation. Furthermore, we contend that even if scalar reward functions can trigger intelligent behaviour in specific cases, it is still undesirable to use this approach for the development of artificial general intelligence due to unacceptable risks of unsafe or unethical behaviour.
Social sites and services rely on the continuing activity, good will and behaviour of the contributors to remain viable. There has been little empirical study of the mechanisms by which social sites ...maintain a viable user base. Such studies would provide a scientific understanding of the patterns that lead to user churn (i.e. users leaving the community) and the community dynamics that are associated with reduction of community members -- primary threats to the sustainability of any service. In this paper, we explore the relation between a user's value within a community - constituted from various user features - and the probability of a user churning.
In this paper, we present a model for competency development using serious games, which is underpinned by a hierarchical case-based planning strategy. In our model, a learner’s objectives are ...addressed by retrieving a suitable learning plan in a two-stage retrieval process. First of all, a suitable abstract plan is retrieved and personalised to the learner’s specific requirements. In the second stage, the plan is incrementally instantiated as the learner engages with the learning material. Each instantiated plan is composed of a series of stories - interactive narratives designed to improve the learner’s competence within a particular learning domain. The sequence of stories in an instantiated plan is guided by the planner, which monitors the learner performance and suggests the next learning step. To create each story, the learner’s competency proficiency and performance assessment history are considered. A new story is created to further progress the plan instantiation. The plan succeeds when the user consistently reaches a required level of proficiency. The successful instantiated plan trace is stored in an experience repository and forms a knowledge base on which introspective learning techniques are applied to justify and/or refine abstract plan composition.
Real-world decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting, objectives. Despite this, the majority of research in reinforcement learning and ...decision-theoretic planning either assumes only a single objective, or that multiple objectives can be adequately handled via a simple linear combination. Such approaches may oversimplify the underlying problem and hence produce suboptimal results. This paper serves as a guide to the application of multi-objective methods to difficult problems, and is aimed at researchers who are already familiar with single-objective reinforcement learning and planning methods who wish to adopt a multi-objective perspective on their research, as well as practitioners who encounter multi-objective decision problems in practice. It identifies the factors that may influence the nature of the desired solution, and illustrates by example how these influence the design of multi-objective decision-making systems for complex problems.
In this paper we describe our novel Twitter assistant called Tadvise. Tadvise helps users to know their Twitter communities better and also assists them to identify community hubs for propagating ...their community-related tweets. Tadvise video describes different parts of Tadvise and how it is used for propagating tweets in Twittersphere.
PDF
