1,721,237 research outputs found
Walter Daelemans
No full textIn this article we provide an overview of recent research on the application of symbolic Machine Learning techniques to language data (Machine Learning of Natural Language, MLNL). Both in Quantitative Linguistics (QL) and in MLNL, the main goal is to describe the language as it is observed with rules, language models, or other descriptions
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
Using Wiktionary to Build an Italian Part-of-Speech Tagger
No full textAbstract: While there has been a lot of progress in Natural Language Processing (NLP), many basic resources are still missing for many languages, including Italian, especially resources that are free for both research and commercial use. One of these basic resources is a Part-of- Speech tagger, a rst processing step in many NLP applications. We describe a weakly-supervised, fast, free and reasonably accurate part-ofspeech tagger for the Italian language, created by mining words and their part-of-speech tags from Wiktionary. We have integrated the tagger in Pattern, a freely available Python toolkit. We believe that our approach is general enough to be applied to other languages as well
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
MINERVA: Benchmarking the detection of musical instruments in unrestricted, non-photorealistic images from the artistic domain
No full textThese folders contains all the data and trained models (including a detailed README), needed to replicate the results from the following publication:
Matthia Sabatelli, Nikolay Banar, Marie Cocriamont, Eva Coudyzer, Karine Lasaracina, Walter Daelemans, Pierre Geurts & Mike Kestemont, "Advances in Digital Music Iconography. Benchmarking the detection of musical instruments in unrestricted, non-photorealistic images from the artistic domain". Digital Humanities Quarterly (2020).
In this paper, we present MINERVA, the first benchmark dataset for the detection of musical instruments in non-photorealistic, unrestricted image collections from the realm of the visual arts. This effort is situated against the scholarly background of music iconography, an interdisciplinary field at the intersection of musicology and art history. We benchmark a number of state-of-the-art systems for image classification and object detection. Our results demonstrate the feasibility of the task but also highlight the significant challenges which this artistic material poses to computer vision. All the corresponding code, necessary for extending or replicating our work, is freely available for reuse (CC-BY) from an open code repository.
This work has been generously funded by the Belgian Federal Research Agency BELSPO under the BRAIN-be program (project title: 'INSIGHT: Intelligent Neural Systems as Integrated Heritage Tools').
Project website: https://hosting.uantwerpen.be/insight
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
Personae: a corpus for author and personality prediction from text
No full textWe present a new corpus for computational stylometry, more specifically authorship attribution and the prediction of author personality from text. Because of the large number of authors (145), the corpus will allow previously impossible studies of variation in features considered predictive for writing style. The innovative meta-information (personality profiles of the authors) associated with these texts allows the study of personality prediction, a not yet very well researched aspect of style. In this paper, we describe the contents of the corpus and show its use in both authorship attribution and personality prediction. We focus on features that have been proven useful in the field of author recognition. Syntactic features like part-of-speech n-grams are generally accepted as not being under the author’s conscious control and therefore providing good clues for predicting gender or authorship. We want to test whether these features are helpful for personality prediction and authorship attribution on a large set of authors. Both tasks are approached as text categorization tasks. First a document representation is constructed based on feature selection from the linguistically analyzed corpus (using the Memory-Based Shallow Parser (MBSP)). These are associated with each of the 145 authors or each of the four components of the Myers-Briggs Type Indicator (Introverted-Extraverted, Sensing-iNtuitive, Thinking-Feeling, Judging-Perceiving). Authorship attribution on 145 authors achieves results around 50 % accuracy. Preliminary results indicate that the first two personality dimensions can be predicted fairly accurately. 1
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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