التفاصيل البيبلوغرافية
العنوان: |
Neural Architecture Comparison for Bibliographic Reference Segmentation: An Empirical Study |
المؤلفون: |
Rodrigo Cuéllar Hidalgo, Raúl Pinto Elías, Juan-Manuel Torres-Moreno, Osslan Osiris Vergara Villegas, Gerardo Reyes Salgado, Andrea Magadán Salazar |
المصدر: |
Data, Vol 9, Iss 5, p 71 (2024) |
بيانات النشر: |
MDPI AG, 2024. |
سنة النشر: |
2024 |
المجموعة: |
LCC:Bibliography. Library science. Information resources |
مصطلحات موضوعية: |
reference mining, BiLSTM, transformers, byte-pair encoding, Conditional Random Fields, Bibliography. Library science. Information resources |
الوصف: |
In the realm of digital libraries, efficiently managing and accessing scientific publications necessitates automated bibliographic reference segmentation. This study addresses the challenge of accurately segmenting bibliographic references, a task complicated by the varied formats and styles of references. Focusing on the empirical evaluation of Conditional Random Fields (CRF), Bidirectional Long Short-Term Memory with CRF (BiLSTM + CRF), and Transformer Encoder with CRF (Transformer + CRF) architectures, this research employs Byte Pair Encoding and Character Embeddings for vector representation. The models underwent training on the extensive Giant corpus and subsequent evaluation on the Cora Corpus to ensure a balanced and rigorous comparison, maintaining uniformity across embedding layers, normalization techniques, and Dropout strategies. Results indicate that the BiLSTM + CRF architecture outperforms its counterparts by adeptly handling the syntactic structures prevalent in bibliographic data, achieving an F1-Score of 0.96. This outcome highlights the necessity of aligning model architecture with the specific syntactic demands of bibliographic reference segmentation tasks. Consequently, the study establishes the BiLSTM + CRF model as a superior approach within the current state-of-the-art, offering a robust solution for the challenges faced in digital library management and scholarly communication. |
نوع الوثيقة: |
article |
وصف الملف: |
electronic resource |
اللغة: |
English |
تدمد: |
2306-5729 |
Relation: |
https://www.mdpi.com/2306-5729/9/5/71; https://doaj.org/toc/2306-5729 |
DOI: |
10.3390/data9050071 |
URL الوصول: |
https://doaj.org/article/8fef86b7779741ff919af74c0cf62e3f |
رقم الانضمام: |
edsdoj.8fef86b7779741ff919af74c0cf62e3f |
قاعدة البيانات: |
Directory of Open Access Journals |