122,649 research outputs found
Veale, N J N, 421059
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/422973Surname: VEALE. Given Name(s) or Initials: N J N. Military Service Number or Last Known Location: 421059. Missing, Wounded and Prisoner of War Enquiry Card Index Number: 51309.249488
Item: [2016.0049.55234] "Veale, N J N, 421059
Once more, with feeling! Using creative affective metaphors to express information needs
No full textCreative metaphors abound in language because they facilitate communication that is memorable, effective and elastic. Such metaphors allow a speaker to be maximally suggestive while being minimally committed to any single interpretation, so they can both supply and elicit information in a conversation. Yet, though metaphors are often used to articulate affective viewpoints and information needs in everyday language, they are rarely used in information retrieval (IR) queries. IR fails to distinguish between creative and uncreative uses of words, since it typically treats words as literal mentions rather than suggestive allusions. We show here how a computational model of affective comprehension and generation allows IR users to express their information needs with creative metaphors that concisely allude to a dense body of assertions. The key to this approach is a lexicon of stereotypical concepts and their affective properties. We show how such a lexicon is harvested from the open web and from local web n-grams
Probabilistic stability assessment of rock excavations
No full textL M Faint, L T Ljubicic, S M Thomson, J R Veale, C Xu, M Karakus and N Melkoumia
II. James (M. K.), Studies m the medieval Wine Trade, éd. by E. M. Veale, Oxford, Clarendon Press, 1971
No full textHigounet Charles. II. James (M. K.), Studies m the medieval Wine Trade, éd. by E. M. Veale, Oxford, Clarendon Press, 1971. In: Annales du Midi : revue archéologique, historique et philologique de la France méridionale, Tome 86, N°116, 1974. pp. 100-101
Revolutionizing support for hospitalized Aboriginal and Torres Strait Islander smokers
No full textStewart S, Marlow N, Chong A, Esterman A, Kopsaftis Z, Sharrad K, Crozier A, Gwilt I, Smith R, Veale A, Brinn M, Carson-Chahhoud
A Multi-Language Comparison of Influences on Author Verification using Character N-Grams
No full textWe create a new multi-language corpus for author verification based on Wikipedia talkpages, and evaluate the influence that differences in topic and time have on character n-gram author profiles. Topic alignment between two texts is found to increase author verification precision, and an authors writing style is found to change over time, but not more significantly after 3 years than after 1 year.Information ArchitectureWISElectrical Engineering, Mathematics and Computer Scienc
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
The vanishing author in computer-generated works: a critical analysis of recent Australian case law
No full textAbstract
The use of software is ubiquitous in the creation of many copyright works, yet the requirement in copyright law that every work have a human author who engages in independent intellectual effort means that its use may prevent copyright subsistence. Several recent Australian cases have refocused attention on authorship as an essential criterion of copyright subsistence, and these cases suggest that much computer-produced output may be authorless and thus lack copyright protection. This article, the first in a two-part series, analyses how each case deals with the question of authorship of computer-produced works and why the use of software diminishes copyright protection for a significant number of computer-generated works. The article critiques the application of conventional notions of human authorship developed in the pre-computer age to modern productions and suggests alternative approaches to authorship that satisfy both the major objectives of copyright policy and the need to adapt to the computer age. The article argues that, without a broader judicial approach to authorship of computer-generated works, Parliament must remedy the lacuna in protection for these ‘authorless’ works. Possible solutions for reform are suggested. In a forthcoming article, the author comprehensively examines those reform proposals
Toward Constructive Optimisation: A new perspective on the regulation of recommender systems and the rights of users and society
No full textHow should we regulate systems designed to optimise digital environments and interactions? One needs to develop at least two critical perspectives to answer such a question. First, relative to what normative standards should optimisation be held? Second, how should regulation understand the tools of optimisation, such as ‘recommender systems’? This study develops an approach to both questions and integrates the corresponding perspectives into one answer. The study is divided into three main parts. In Part 1 a normative framework – centred around the values of self-development and self-determination – is elaborated as an interpretational resource to understand better how optimisation can be meaningful. When it comes to recommender systems, there is a need to move beyond naïve approaches, which implicitly assume that ‘the recommender system’ is an identifiable, discrete ‘unit’ that can be addressed and regulated as such. Instead, we propose to conceptualise and evaluate recommender systems through a so-called “stack approach”. This is the purpose of Part 2. The envisaged “stack approach” embraces the insight that beyond the surface interface level, recommender services are the result of different interactions, operations and layers, that are both social and technical in nature — software, hardware, infrastructure, organisational, design principles, and so on. All these parts work in concert to, ultimately, create particular tools, interfaces, and functionalities. Finally, Part 3 combines the normative framework of Part 1 and the stack approach of Part 2 for a critical analysis of the current approach to the regulation of recommender systems under the DSA, and for developing constructive suggestions of how to better account for the legitimate interests of users and society. Recommender systems should be regulated addressing every layer of the stack. Put simply, analysing and regulating the recommender system is not (only) about analysing and regulating the actual recommender engine, i.e., the software systems designed to fulfil optimisation logics, or the interface people interact with. The net should be cast wider. Optimisation goals determined by management, KPIs determined by business departments, performance reviews, hiring practices, data collection and analysis practices, iterative software design philosophies, UX/UI design choices, data training models, and so on, should all be incorporated into the bread and butter of recommender system regulation. This study, then, combines a more realistic, helpful approach to recommender systems as socio-technical artefacts with an original theoretical perspective on the normative standards we should hold optimisation systems to. In this report, we formulate a set of overarching recommendations that could guide future regulatory amendments. In an upcoming update and annex to this report, we will take up this exercise ourselves, and demonstrate how our model can be translated into concrete regulatory provisions. At the same time, we offer the stack approach as a toolkit to the reader: a starting point for reflection toward a more healthy and fair digital eco-system. In this context, it should be noted from the outset that the more realistic stack approach can be as enlightening as it can be overwhelming. The benefit of the approach is that it allows for a very wide, structural approach that cuts across the entire recommender value-chain or stack to show how a wide range of EU legislation can be used to regulate various elements of this ecosystem. The resulting analysis can, at the same time, also lead to what feels like a rather fragmented story – at least in terms of presentation. To further add to this enlightening complexity, the stack approach allows one to address separate layers of the stack individually, but one can also show how several layers (can) interact with one another in the regulatory context, or how ‘whole stack provisions’ address the entire stack. In short, the stack’s analytical modularity allows for a very all-encompassing mosaic approach that can address several analytical levels at the same time. Its inherent complexity is a feature, not a bug. This should be kept in mind when reading this exploratory study
Toward Constructive Optimisation: A new perspective on the regulation of recommender systems and the rights of users and society
No full textHow should we regulate systems designed to optimise digital environments and interactions? One needs to develop at least two critical perspectives to answer such a question. First, relative to what normative standards should optimisation be held? Second, how should regulation understand the tools of optimisation, such as ‘recommender systems’? This study develops an approach to both questions and integrates the corresponding perspectives into one answer. The study is divided into three main parts. In Part 1 a normative framework – centred around the values of self-development and self-determination – is elaborated as an interpretational resource to understand better how optimisation can be meaningful. When it comes to recommender systems, there is a need to move beyond naïve approaches, which implicitly assume that ‘the recommender system’ is an identifiable, discrete ‘unit’ that can be addressed and regulated as such. Instead, we propose to conceptualise and evaluate recommender systems through a so-called “stack approach”. This is the purpose of Part 2. The envisaged “stack approach” embraces the insight that beyond the surface interface level, recommender services are the result of different interactions, operations and layers, that are both social and technical in nature — software, hardware, infrastructure, organisational, design principles, and so on. All these parts work in concert to, ultimately, create particular tools, interfaces, and functionalities. Finally, Part 3 combines the normative framework of Part 1 and the stack approach of Part 2 for a critical analysis of the current approach to the regulation of recommender systems under the DSA, and for developing constructive suggestions of how to better account for the legitimate interests of users and society. Recommender systems should be regulated addressing every layer of the stack. Put simply, analysing and regulating the recommender system is not (only) about analysing and regulating the actual recommender engine, i.e., the software systems designed to fulfil optimisation logics, or the interface people interact with. The net should be cast wider. Optimisation goals determined by management, KPIs determined by business departments, performance reviews, hiring practices, data collection and analysis practices, iterative software design philosophies, UX/UI design choices, data training models, and so on, should all be incorporated into the bread and butter of recommender system regulation. This study, then, combines a more realistic, helpful approach to recommender systems as socio-technical artefacts with an original theoretical perspective on the normative standards we should hold optimisation systems to. In this report, we formulate a set of overarching recommendations that could guide future regulatory amendments. In an upcoming update and annex to this report, we will take up this exercise ourselves, and demonstrate how our model can be translated into concrete regulatory provisions. At the same time, we offer the stack approach as a toolkit to the reader: a starting point for reflection toward a more healthy and fair digital eco-system. In this context, it should be noted from the outset that the more realistic stack approach can be as enlightening as it can be overwhelming. The benefit of the approach is that it allows for a very wide, structural approach that cuts across the entire recommender value-chain or stack to show how a wide range of EU legislation can be used to regulate various elements of this ecosystem. The resulting analysis can, at the same time, also lead to what feels like a rather fragmented story – at least in terms of presentation. To further add to this enlightening complexity, the stack approach allows one to address separate layers of the stack individually, but one can also show how several layers (can) interact with one another in the regulatory context, or how ‘whole stack provisions’ address the entire stack. In short, the stack’s analytical modularity allows for a very all-encompassing mosaic approach that can address several analytical levels at the same time. Its inherent complexity is a feature, not a bug. This should be kept in mind when reading this exploratory study
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