1,721,032 research outputs found
Spatial data on the web: Issues and challenges
No full textSpatial data are today needed in a wide range of application domains. Indeed, spatial properties are included in several application contexts requiring the management of very large data sets, such as, for instance, computer-aided design (CAD), very large scale integration (VLSI), robotics, and image processing. However, the primary target of systems dealing with spatial data remains geographical applications, since they served as the first motivation for the development of such technology and still represent the most challenging application environment [19]. Spatial data can be defined as pieces of information describing quantitative and/or qualitative properties that refer to space. Such properties can be represented as attributes of a set of objects (like the path of a given highway or the technical drawing of the new version of a car engine) or as functions of the space locations (like the temperature measured at a given location on the European continent or the measured infrared emissions in a remote sensing image). © Springer-Verlag Berlin Heidelberg 2007. All rights are reserved
Coverage-based Queries: Nondiscrimination Awareness in Data Transformation
No full textWhen people-related data are used in automated decision making processes, social inequities can be amplified. Thus, the development of technological solutions satisfying nondiscrimination requirements, in terms of, e.g., fairness, diversity, and coverage, is currently one of the main challenges for the data management and data analytics communities. In particular, coverage constraints guarantee that a dataset includes enough items for each (protected) category of interest, thus increasing diversity with the aim of limiting the introduction of bias during the next analytical steps. While coverage constraints have been mainly used for designing data repair solutions, in our study we investigate their effects on data processing pipelines, with a special reference to data transformation. To this aim, we first introduce coverage-based queries as a means for ensuring coverage constraint satisfaction on a selection-based query result, through rewriting. We then present two approximate algorithms for coverage-based query processing: the first, covRew, initially introduced in [3], relies on data discretization and sampling; the second, covKnn is a novel contribution and relies on a nearest neighbour approach for coverage-based query processing. The algorithms are experimentally compared with respect to efficiency and effectiveness, on a real dataset
Coverage-based rewriting for data preparation
No full textThe development of technological solutions satisfying non discriminating requirements is currently one of the main challenges for data processing. Concepts like fairness, i.e., lack of bias, and diversity, i.e., the degree to which different kinds of objects are represented in a dataset, have been recently taken into account in designing non-discriminating set selection, ranking, and OLAP approaches. Information extraction is however also at the basis of back-end data processing, for preparing, e.g., extracting and transforming data, usually based on SQL queries, before loading them inside a data warehouse for further front-end processing. The impact of an unfair data preparation process might have a relevant impact on front-end analysis. As an example, an underrepresented category in the warehouse might lead to an underrepresentation of that category in most of the following processes. This kind of guarantee is known as coverage. In this paper, we start from this consideration and we propose an approach for automatically rewriting back-end queries, whose results do not guarantee some coverage constraints, into the "closest" queries satisfying those constraints. Through rewriting, coverage-based modifications of data preparation steps are traced for further processing. We also present some preliminary experimental results and we identify some directions for future works
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
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