1,720,983 research outputs found
MEMEX_KG: Knowledge Graphs about the cities of Lisbon, Barcelona and Paris
No full textKnowledge Graphs about the cities of Lisbon, Barcelona and Paris. The datasets are used in the following paper:
Mohamed, Hebatallah A., Sebastiano Vascon, Feliks Hibraj, Stuart James, Diego Pilutti, Alessio Del Bue, and Marcello Pelillo. "Geolocation of Cultural Heritage using Multi-View Knowledge Graph Embedding." arXiv preprint arXiv:2209.03638 (2022)
Using Dominant Sets for k-NN Prototype Selection
No full textk-Nearest Neighbors is surely one of the most important and widely adopted non-parametric classification methods in pattern recognition. It has evolved in several aspects in the last 50 years, and one of the most known variants consists in the usage of prototypes: a prototype distills a group of similar training points, diminishing drastically the number of comparisons needed for the classification; actually, prototypes are employed in the case the cardinality of the training data is high. In this paper, by using the dominant set clustering framework, we propose four novel strategies for the prototype generation, allowing to produce representative prototypes that mirror the underlying class structure in an expressive and effective way. Our strategy boosts the k-NN classification performance; considering heterogeneous metrics and analyzing 15 diverse datasets, we are among the best 6 prototype-based k-NN approaches, with a computational cost which is strongly inferior to all the competitors. In addition, we show that our proposal beats linear SVM in the case of a pedestrian detection scenario
Detecting conversational groups in images and sequences: a robust game-theoretic approach
Full text linkDetecting groups is becoming of relevant interest as an important step for scene (and especially activity) understanding. Differently from what is commonly assumed in the computer vision community, different types of groups do exist, and among these, standing conversational groups (a.k.a. F-formations) play an important role. An F-formation is a common type of people aggregation occurring when two or more persons sustain a social interaction, such as a chat at a cocktail party. Indeed, detecting and subsequently classifying such an interaction in images or videos is of considerable importance in many applicative contexts, like surveillance, social signal processing, social robotics or activity classification, to name a few. This paper presents a principled method to approach to this problem grounded upon the socio-psychological concept of an F-formation. More specifically, a game-theoretic framework is proposed, aimed at modeling the spatial structure characterizing F-formations. In other words, since F-formations are subject to geometrical configurations on how humans have to be mutually located and oriented, the proposed solution is able to account for these constraints while also statistically modeling the uncertainty associated with the position and orientation of the engaged persons. Moreover, taking advantage of video data, it is also able to integrate temporal information over multiple frames utilizing the recent notions from multi-payoff evolutionary game theory. The experiments have been performed on several benchmark datasets, consistently showing the superiority of the proposed approach over the state of the art, and its robustness under severe noise conditions
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
Protein function prediction as a graph-transduction game
Full text linkMotivated by the observation that network-based methods for the automatic prediction of protein functions can greatly benefit from exploiting both the similarity between proteins and the similarity between functional classes (as encoded, e.g., in the Gene Ontology), in this paper we propose a novel approach to the problem, based on the notion of a “graph transduction game.” We envisage a (non-cooperative) game, played over a graph, where the players (graph vertices) represent proteins, the functional classes correspond to the (pure) strategies, and protein- and function-level similarities are combined into a suitable payoff function. Within this formulation, Nash equilibria turn out to provide consistent functional labelings of proteins, and we use classical replicator dynamics from evolutionary game theory to find them. To test the effectiveness of our approach we conducted experiments on five different organisms and three ontologies, and the results obtained show that our method compares favorably with state-of-the-art algorithms
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