1,720,956 research outputs found
Identifikasi Informasi Prosedural dari Berita Menggunakan Model Hibrid Berbasis Transformer dan Teknik Oversampling
No full textInformasi prosedural, yang menjelaskan proses atau metode bagaimana suatu peristiwa terjadi, merupakan informasi yang sangat berharga di berbagai bidang seperti pendidikan, jurnalisme, dan penelitian. Meskipun kemajuan (Natural Language Processing) NLP telah memungkinkan untuk mengklasifikasikan teks dengan lebih cepat dan akurat, penelitian terkait identifikasi informasi prosedural pada berita masih terbatas. Sebagian besar studi sebelumnya berfokus pada dokumen teknis, manual pengguna, atau ilmiah yang terstruktur dan eksplisit, sementara teks berita bersifat naratif dan deskriptif, dengan informasi prosedural yang sering tersirat dan tersebar yang menjadikan proses identifikasi menjadi lebih sulit. Untuk menjawab permasalahan tersebut, penelitian ini mengusulkan pendekatan baru dengan menggabungkan dua model berbasis Transformer, untuk menghasilkan representasi fitur semantik pada level kalimat dan level kontekstual. Kedua representasi fitur tesebut digabungkan untuk dimanfaatkan dalam identifikasi apakah kalimat tersebut mengandung unsur prosedural atau tidak. Selain itu, teknik oversampling menggunakan model Text-To-Text Transfer Transformer (T5) diterapkan pada kelas minoritas dalam dataset pelatihan untuk memperkaya variasi data dan meningkatkan kinerja pelatihan model. Hasil eksperimen menunjukkan bahwa gabungan model terbaik yaitu XLNet + RoBERTa dengan pendekatan hirarkis, mencapai F1-score sebesar 75,33%, mengungguli baik single maupun hybrid model lainnya. Pendekatan ini menunjukkan potensi signifikan untuk meningkatkan kinerja identifikasi informasi prosedural dari teks berita.
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Procedural information, which describes the processes or methods by which an event occurs, is highly valuable in various fields such as education, journalism, and research. Although advancements in Natural Language Processing (NLP) have enabled faster and more accurate for text classification, research on detecting procedural information from news texts remains limited. Most previous studies have focused on technical documents, user manuals, or scientific texts that are structured and explicit. In contrast, news texts are narrative and descriptive, with procedural information often being implicit and scattered, making the identification process more challenging. To address this issue, this study proposes a novel approach by combining two Transformer-based models to generate semantic feature representations at both the sentence and contextual levels. These representations are then combined to identify whether a sentence contains procedural elements. Additionally, an oversampling technique using the Text-To-Text Transfer Transformer (T5) model is applied to the minority class in the training dataset to enrich data variation and improve model performance. The experimental results demonstrate that the best-performing model combination, XLNet + RoBERTa, achieved an F1-score of 75,33% using a hierarchical approach, outperforming other single and hybrid models. This approach shows significant potential to enhance the accuracy of procedural information identification from news texts
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
Rancang Bangun Aplikasi Drone Simulator Berbasis Android Menggunakan Game Engine Unity
Full text linkkoamabayili/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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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