1,720,957 research outputs found
Sequent calculi and an efficient theorem prover for conditional logics with selection function semantics
No full textIn this paper we present our final solution to the problem of designing an efficient theorem prover for Conditional Logics with the selection function semantics. Conditional Logics recently have received a renewed attention and have found several applications in knowledge representation and artificial intelligence. In order to provide an efficient theorem prover for Conditional Logics, we introduce labelled sequent calculi for the logics characterized by well-established axioms systems including the axiom of strong centering CS, the axiom of conditional identity ID, the axiom of conditional modus ponens MP, as well as the conditional third excluded middle CEM, rejected by Lewis but endorsed by Stalnaker, as well as for the whole cube of extensions. The proposed calculi revise and improve the calculi SeqS introduced in Olivetti et al. (2007, ACM Trans. Comput. Logics, 8). We also present an implementation of these calculi in SWI Prolog, including a graphical interface in Python as well as standard heuristics and refinements that allow us to obtain an efficient theorem prover for the logics under consideration. Moreover, we present some statistics about the performances of the theorem prover, which are promising and significantly better than those of its predecessor CondLean, an implementation of the calculi SeqS
Body-Shaming Detection and Classification in Italian Social Media
Full text linkIn the last decades, the Natural Language Processing (NLP) community has demonstrated committed involvement in addressing societal challenges, particularly in the realm of hate-speech detection. Despite advancements, these phenomena continue to perpetrate, especially online, where users on social network platforms often find themselves in unsafe and possibly harmful environments. Among the various manifestations of hate speech and offensive language, one aspect that has been overlooked by the NLP community is body-shaming. Despite its prevalence among hateful users and its potential to harm a diverse group of individuals, from women to people with disabilities, efforts to counteract this damaging phenomenon remain limited. In this work, we first introduce a novel taxonomy designed to distinguish and classify instances of body-shaming by the targeted group. Following this, we present a dataset of Instagram comments for body-shaming detection and classification in the Italian language, which has been manually annotated according to the taxonomy. After detailing the data-gathering and annotation process, we present a classification benchmark using three BERT-based models to showcase our dataset’s classification potential. Results demonstrate good performances in detecting body-shaming instances across several categories of our proposed taxonomy
Learning Typicality Inclusions in a Probabilistic Description Logic for Concept Combination
Full text linkOur paper introduces an innovative automated system designed to extract logical rules using the T-CL logic from diverse datasets, with a particular emphasis on tabular data. Our starting point is the CN2 algorithm. Typically employed for classification tasks, we have adapted this algorithm to suit our descriptive objectives. We consider well-known datasets (such as iris and zoo) to illustrate our approach. Furthermore, we extend this analysis to intricate datasets, notably the GTZAN musical dataset and the "Adult" dataset. These examples showcase the algorithm's efficacy in generating descriptive rules across different data domains. We discuss the adaptability of the proposed approach across various data types, including images, sounds, and diverse heterogeneous structures
Combining neural and symbolic approaches to solve the Picasso problem: A first step
No full textIn this work we create a bridge between Convolutional Neural Networks and Answer Set Programming in order to tackle the known Picasso Problem in the automated detection of images. The basic idea is to first exploit the main features of the neural network approach for image recognition, and then to address the problem of identifying well-formed (not meshed up) images by means of explicit knowledge expressed by logical rules. Preliminary experiments suggest that the proposed approach is promising and can be considered as a first step in the direction of solving the Picasso Problem, as well as a witness of the benefits that can be obtained by the combination of a neural approach with a pure symbolic one
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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