The large number of Web pages on many Web sites has raised\ud navigational problems. Markov chains have recently been used to model user navigational behavior on the World Wide Web (WWW). In this paper, we propose a method for constructing a Markov model of a Web site based on past\ud visitor behavior. We use the Markov model to make link predictions that assist new users to navigate the Web site. An algorithm for transition probability\ud matrix compression has been used to cluster Web pages with similar transition behaviors and compress the transition matrix to an optimal size for efficient probability calculation in link prediction. A maximal forward path method is used to further improve the efficiency of link prediction. Link prediction has been implemented in an online system called ONE (Online Navigation Explorer) to assist users' navigation in the adaptive Web site.
Publisher: The WAC Clearinghouse; University Press of Colorado
Drawing on critical realism, complexity theory, and emergence, this chapter supports the call to re-imagine doctoral writing by arguing that academic writing in general is a complex open and emergent social system that can change. Several reasons to re-imagine doctoral writing are discussed. The first reason is that academic writings already exhibit considerable diversity. This suggests that the conditions of possibility for re-imagining them are already in place and provide a conceptual space from which to further imagine. Second, there are\ud epistemic reasons for re-thinking how we write, as evidenced by research on socio-semiotics. Several examples of doctoral writers\ud who have re-imagined their writing for epistemic reasons are given. To explain how change in social phenomena is possible and how it can continue to be justified, I draw on the theory of complex permeable open systems. These systems are emergent and, as such, allow us to think of social phenomena, such as writing, as non-reductive organic unities whose characteristics emerge from but cannot be reduced to any single constituent feature (such as grammar or lexis). By re-thinking academic writings in this way, we can provide a rationale to explain how they can continue to change. The chapter concludes by sharing the work of scholars engaged in re-imagining doctoral writings. The significance for writing studies is that critical realism offers a systematic and critical space within which to explain change\ud in social phenomena and provides a theoretical foundation for continuing to re-imagine conditions of possibility.
Part 12: Workshops; International audience; The manipulation of information and the dissemination of “fake news” are practices that trace back to the early records of human history. Significant changes in the technological environment enabling ubiquity, immediacy and considerable anonymity, have facilitated the spreading of misinformation in unforeseen ways, raising concerns around people’s (mis)perception of social issues worldwide. As a wicked problem, limiting the harm caused by misinformation goes beyond technical solutions, requiring also regulatory and behavioural changes. This workshop proposes to unpack the challenge at hand by bringing together diverse perspectives to the problem. Based on participatory design principles, it will challenge participants to critically reflect the limits of existing socio-technical approaches and co-create scenarios in which digital platforms support misinformation resilience.
Project: UKRI | Automatic Adaptation of K... (EP/F035357/1), UKRI | Automatic Adaptation of K... (EP/F035357/1)
User evaluations of search engines are expensive and not easy to replicate. The problem is even more pronounced when assessing adaptive search systems, for example system-generated query modification suggestions that can be derived from past user interactions with a search engine. Automatically predicting the performance of different modification suggestion models before getting the users involved is therefore highly desirable. AutoEval is an evaluation methodology that assesses the quality of query modifications generated by a model using the query logs of past user interactions with the system. We present experimental results of applying this methodology to different adaptive algorithms which suggest that the predicted quality of different algorithms is in line with user assessments. This makes AutoEval a suitable evaluation framework for adaptive interactive search engines.
In this chapter we explore the future for innovation in two related, but distinct, sectors. We consider the linkages between medical technology(MedTech) and agricultural technology (Agri-Tech) innovation in the UK. We ask and discuss questions: Who are the key actors in the innovation systems of Medtech and Agri-Tech in the UK? What are the core technologies driving the current waves of innovation in these two sectors? Can one industry learn from the other? Where is the scope for cooperation and synergies? We notice that both sectors are technologically linked through foundational technologies underpinning the majority of the observed innovation e.g. big data, AI, IoT and robotics. The outputs of these technologies rely crucially on digital data for insight and decision support. However, Agri-Tech benefits from less complex stakeholder issues regarding data security and privacy. Both sectors are important to the UK going forwards, and both will be exposed to Brexit and the consequences of the COVID pandemic. Our discussion on the future of innovation should be of particular interest to start-up leaders, entrepreneurs, investors, managers and policy-makers in MedTech, Agri-Tech and cognate sectors.
Classifying research papers according to their research topics is an important task to improve their retrievability, assist the creation of smart analytics, and support a variety of approaches for analysing and making sense of the research environment. In this paper, we present the CSO Classifier, a new unsupervised approach for automatically classifying research papers according to the Computer Science Ontology (CSO), a comprehensive ontology of re-search areas in the field of Computer Science. The CSO Classifier takes as input the metadata associated with a research paper (title, abstract, keywords) and returns a selection of research concepts drawn from the ontology. The approach was evaluated on a gold standard of manually annotated articles yielding a significant improvement over alternative methods. Comment: Conference paper at TPDL 2019
Publisher: Dept. of Mining Engineering, College of Engineering and Mineral Resources, West Virginia University
Country: United Kingdom
Since the advent of New Austrian Tunneling Method (NATM), shotcrete as a primary means of support in tunnels has been widely applied. It’s most important features are durability, speed of application and cost effectiveness. This paper introduces some tables that provide guidelines for the thickness of shotcrete required in some common situations of mine roadways. In order to devise such tables, two different arch sections, together with three different overburden types, were considered. Geotechnical parameters such as apparent cohesion and angle of internal friction of surrounding rocks were chosen, based on the five-category classification of Bieniawski. Two K0 factors (the ratio of horizontal stress to vertical stress) and an average rock density were utilized. Using numerical methods, 60 models were then devised in this way. By applying interaction diagrams of axial force and the bending moment for different thicknesses of shotcrete, appropriate shotcrete thickness for these models were calculated. The results of this research, as well as the methodology applied, can be used in mining roadway support design and all types of civil engineering tunnels.
Publication . Part of book or chapter of book . Article . Conference object . 2011
Understanding and forecasting the health of an online community is of great value to its owners and managers who have vested interests in its longevity and success. Nevertheless, the association between community evolution and the behavioural patterns and trends of its members is not clearly understood, which hinders our ability of making accurate predictions of whether a community is flourishing or diminishing. In this paper we use statistical analysis, combined with a semantic model and rules for representing and computing behaviour in online communities. We apply this model on a number of forum communities from Boards.ie to categorise behaviour of community members over time, and report on how different behaviour compositions correlate with positive and negative community growth in these forums.
We present a logic for reasoning about state transition systems (LOTOS behaviours) which allows properties involving repeated patterns over actions and data to be expressed, The state transition systems are derived from LOTOS behaviours; however, the logic is applicable to any similar formalism. The semantics of the logic is given with respect to symbolic transition systems, allowing reasoning about data to be separated from reasoning about flow of control. Several motivational examples are included.