1,721,235 research outputs found
Faster OWL Using Split Programs
No full textare sought to cope with large ABoxes in an approximate manner. The idea is to use quick heuristic reasoning when time constraints are more important than the correctness of the answers. A typical use case is online question answering, where it is more important to give rough answers quickly than to have precise responses at the cost of long delays. # Pascal Hitzler is supported by the German Federal Ministry of Education and Research (BMBF) under the SmartWeb project, and by the European Union under the KnowledgeWeb Network of Excellence. + Denny Vrandecic is supported by the European Commission under contract IST-2003-506826 SEKT. The expressed content is the view of the authors but not necessarily the view of the SEKT project as a whole. 2 From OWL to datalog The approach which we propose is based on the fact that data complexity is polynomial for non-disjunctive datalog. We utilise recent research results about the transformation of OWL DL ontologies into disjunctive datal
Faster OWL Using Split Programs
Get PDFKnowledge representation and reasoning on the Semantic Web is done by means of ontologies. While the quest for suitable ontology languages is still ongoing, OWL [5] has been established as a core standard. It comes in three flavours, as OWL Full, OWL DL and OWL Lite, where OWL Full contains OWL DL, which in turn contains OWL Lite. The latter two coincide semantically with certain description logics and can thus be considered fragments of first-order predicate logic
Description Logic Programs: A Practical Choice for the Modelling of Ontologies
Get PDFKnowledge representation using ontologies constitutes the heart of semantic technologies. Despite successful standardization efforts by the W3C, however, there are still numerous different ontology representation languages being used, and interoperability between them is in general not given. The problem is aggrevated by the fact that current standards lay foundations only and are well-known to be insufficient for the modelling of finer details. Thus, a plethora of extensions of the basic languages is being proposed, rendering the picture of ontology representation languages to be chaotic, to say the least. While semantic technologies start to become applicable and are being applied in adjacent areas of research and in research projects with industrial participation, and can soon be expected to become an integral part of industrial applications, the practitioner is faced with the difficult task of choosing his basic ontology representation paradigm. We will argue that the OWL subset known as Description Logic Programs constitutes a very reasonable choice
Knowledge-aware Interpretable Recommender Systems
No full textRecommender systems are everywhere, from e-commerce to streaming platforms. They help users lost in the maze of available information, items, and services to find their way. Among them, over the years, approaches based on machine learning techniques have shown particularly good performance for top-N recommendations engines. Unfortunately, they mostly behave as black-boxes and, even when they embed some form of description about the items to recommend, after the training phase they move such descriptions in a latent space thus loosing the actual explicit semantics of recommended items. As a consequence, the system designers struggle at providing satisfying explanations to the recommendation list provided to the end-user. In this chapter, we describe two approaches to recommendation which make use of the semantics encoded in a knowledge graph to train interpretable models which keep the original semantics of the items description thus providing a powerful tool to automatically compute explainable results. The two methods relies on two completely different machine learning algorithms, namely, factorization machines and autoencoder neural networks. We also show how to measure the interpretability of the model through the introduction of two metrics: semantic accuracy and robustness
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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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