1,720,958 research outputs found
A Preliminary Study on the Application of Reinforcement Learning for Predictive Process Monitoring
No full textThe present paper explores the opportunity of applying reinforcement learning to various typical tasks in the field of predictive process monitoring. The tasks considered are the prediction of both nextevent activity and time completion as well as the prediction of the whole progression of running cases. Experiments have been conducted on the popular benchmark dataset, BPI’ 2012, on which we compare the pro-posed learning system with state of the art methods adopting LSTM networks trained through supervised learning. Results enlighten promising features of the approach and interesting research issues and challenges, as well as proving the applicability of reinforcement learning to predictive process monitoring
An Experimental Comparison of Large Language Models for Emotion Recognition in Italian Tweets
No full textIn recent years, the advent of Large Language Models (LLMs), which are task-agnostic models trained on huge amounts of textual data, has given momentum to a wide variety of NLP applications, ranging from chatbots to sentiment classifiers. Currently, many LLMs are publicly available, each with different features and performance, and the selection of the best LLM for a specific task may be challenging. In this work, we focus on the task of emotion recognition in Italian social media content and we present an experimental comparison among three of the most popular LLMs: Google Bidirectional Encoder Representations from Transformers (BERT), OpenAI Generative Pre-trained Transformer 3 (GPT-3) and GPT-3.5. Model specialization in emotion recognition has been achieved by using two different approaches, namely fine-tuning and prompt engineering with few-shot task transfer. The experimentation has been performed on TwIT, a corpus of about 3100 Italian tweets annotated with respect to six emotions. The results show that fine-tuning GPT-3 leads to the best performance on the considered dataset, achieving a remarkable F1=0.90
Evidence-driven appraisal of students’ careers using process mining: a case study
Full text linkToday’s universities are more and more focused on improving their educational programs and supporting their students throughout their academic journey. A key aspect of such an effort is understanding which factors contribute to poor students’ performance. This research illustrates how educational process mining techniques can be used to effectively uncover success and failure factors in students’ academic journeys through a case study at an Italian university. The research reveals patterns related to adherence to curriculum requirements, strategies for taking exams, and the influence of various factors, such as the number of exams passed in the first year on graduation timelines. These findings offer valuable insights for educational institutions that might be used to, e.g., implement support mechanisms to enhance students’ overall success rates
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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