1,720,959 research outputs found

    Digging into prerequisite annotation

    No full text
    Intelligent textbooks are often engineered with an explicit representation of their concepts and prerequisite relations (PR). PR identification is hence crucial for intelligent textbooks but still presents some challenges, also when performed by human experts. This may cause PR-annotated datasets to be inconsistent and compromise the accuracy of automatic creation of enhanced learning materials. This paper investigates possible reasons for PR disagreement and the nature of PR itself, with the aim of contributing to the development of shared strategies for PR annotation, analysis and modelling in textbooks

    PRET: Prerequisite-enriched terminology. A case study on educational texts

    No full text
    In this paper we present PRET, a gold dataset annotated for prerequisite relations between educational concepts extracted from a computer science textbook, and we describe the language and domain independent approach for the creation of the resource. Additionally, we have created an annotation tool to support, validate and analyze the annotation

    Visualisation analysis for exploring prerequisite relations in textbooks

    No full text
    Building automatic strategies for organising knowledge contained in textbooks has a tremendous potential to enhance meaningful learning. Automatic identification of prerequisite relation (PR) between concepts in a textbook is a well-known way for knowledge structuring, yet it is still an open issue. Our research contributes for better understanding and exploring the phenomenon of PR in textbooks, by providing a collection of visualisation techniques for PR exploration and analysis, that we used for the design of and then the refinement of our algorithm for PR extraction

    PRELEARN @ EVALITA 2020: Overview of the prerequisite relation learning task for Italian

    No full text
    The Prerequisite Relation Learning (PRELEARN) task is the EVALITA 2020 shared task on concept prerequisite learning, which consists of classifying prerequisite relations between pairs of concepts distinguishing between prerequisite pairs and non-prerequisite pairs. Four sub-tasks were defined: two of them define different types of features that participants are allowed to use when training their model, while the other two define the classification scenarios where the proposed models would be tested. In total, 14 runs were submitted by 3 teams comprising 9 total individual participants

    Green balance in urban areas as an indicator for policy support: a multi-level application

    Full text link
    Green spaces are increasingly recognised as key elements in enhancing urban resilience as they provide several ecosystem services. Therefore, their implementation and monitoring in cities are crucial to meet sustainability targets. In this paper, we provide a methodology to compute an indicator that assesses changes in vegetation cover within Urban Green Infrastructure (UGI). Such an indicator is adopted as one of the indicators for reporting on the key area “nature and biodiversity” in the Green City Accord (GCA). In the first section, the key steps to derive the indicator are described and a script, which computes the trends in vegetation cover using Google Earth Engine (GEE), is provided. The second section describes the application of the indicator in a multi-scale, policy-orientated perspective. The analysis has been carried out in 696 European Functional Urban Areas (FUAs), considering changes in vegetation cover inside UGI between 1996 and 2018. Results were analysed for the EU and the United Kingdom. The Municipality of Padua (Italy) is used as a case study to illustrate the results at the local level. Over the last 22 years, a slight upward trend characterised the vegetation growth within UGI in European FUAs. Within core cities and densily built-upcommuting zones, the trend was stable; in non-densely built-up areas, an upward trend was recorded. Vegetation cover in UGI has been relatively stable in European cities. However, a negative balance between abrupt changes in greening and browning has been recorded, affecting most parts of European cities (75% of core cities and 77% of commuting zones in densely built-up areas). This still indicates ongoing land take with no compensation of green spaces that are lost to artificial areas. Focusing on the FUA of Padua, a downward trend was observed in 33.3% and 12.9% of UGI in densely built-up and not-densely built-up areas, respectively. Within the FUA of Padua, most municipalities are characterised by a negative balance between abrupt greening and browning, both in non-densely built-up and densely built-up areas. This approach complements traditional metrics, such as the extent of UGI or tree canopy cover, by providing a valuable measure of condition of urban ecosystems and an instrument to monitor the impact of land take

    Going Beyond Counting First Authors in Author Co-citation Analysis

    Full text link
    The 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

    Towards the Identification of Propaedeutic Relations in Textbooks

    No full text
    As well-known, structuring knowledge and digital content has a tremendous potential to enhance meaningful learning. A straightforward approach is representing key concepts of the subject matter and organizing them in a knowledge structure by means of semantic relations. This results in hypergraphs with typed n-ary relationships, including the so-called prerequisite or propaedeutic relations among concepts. While extracting the whole concept graph from a textbook is our final goal, the focus of this paper is the identification of the propaedeutic relations among concepts. To this aim, we employ a method based on burst analysis and co-occurrence which recognizes, by means of temporal reasoning, prerequisite relations among concepts that share intense periods in the text. The experimental evaluation shows promising results for the extraction of propaedeutic relations without the support of external knowledge

    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 link
    We 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
    corecore