1,720,967 research outputs found
rmassidda @ DaDoEval: Document Dating Using Sentence Embeddings at EVALITA 2020
This report describes an approach to solve the DaDoEval document dating subtasks for the EVALITA 2020 competition. The dating problem is tackled as a classification problem, where the significant length of the documents in the provided dataset is addressed by using sentence embeddings in a hierarchical architecture. Three different pre-trained models to generate sentence embeddings have been evaluated and compared: USE, LaBSE and SBERT. Other than sentence embeddings the classifier exploits a bag-of-entities representation of the document, generated using a pre-trained named entity recognizer. The final model is able to simultaneously produce the required date for each subtask
Knowledge-Driven Interpretation of Convolutional Neural Networks
Since the widespread adoption of deep learning solutions in critical environments, the interpretation of artificial neural networks has become a significant issue. To this end, numerous approaches currently try to align human-level concepts with the activation patterns of artificial neurons. Nonetheless, they often understate two related aspects: the distributed nature of neural representations and the semantic relations between concepts. We explicitly tackled this interrelatedness by defining a novel semantic alignment framework to align distributed activation patterns and structured knowledge. In particular, we detailed a solution to assign to both neurons and their linear combinations one or more concepts from the WordNet semantic network. Acknowledging semantic links also enabled the clustering of neurons into semantically rich and meaningful neural circuits. Our empirical analysis of popular convolutional networks for image classification found evidence of the emergence of such neural circuits. Finally, we discovered neurons in neural circuits to be pivotal for the network to perform effectively on semantically related tasks. We also contribute by releasing the code that implements our alignment framework
Gold stripping by hydro-alcoholic solutions from activated carbon: experimental results and data analysis by a semi-empirical model
Gold stripping by hydro-alcoholic solutions from activated carbon: experimental results and data analysis by a semi-empirical model
Going Beyond Counting First Authors in Author Co-citation Analysis
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
Variations on the Author
“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
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
Causal Abstraction with Soft Interventions
Causal abstraction provides a theory describing how several causal models can
represent the same system at different levels of detail. Existing theoretical
proposals limit the analysis of abstract models to "hard" interventions fixing
causal variables to be constant values. In this work, we extend causal
abstraction to "soft" interventions, which assign possibly non-constant
functions to variables without adding new causal connections. Specifically, (i)
we generalize -abstraction from Beckers and Halpern (2019) to soft
interventions, (ii) we propose a further definition of soft abstraction to
ensure a unique map between soft interventions, and (iii) we prove
that our constructive definition of soft abstraction guarantees the
intervention map has a specific and necessary explicit form
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