Mapping Researcher Activity based on Publication Data by means of Transformers

Autor:	Bettouche, Zineddine, Fischer, Andreas
Rok vydání:	2023
Předmět:	Computer Science - Computation and Language Computer Science - Digital Libraries Computer Science - Information Retrieval Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	Modern performance on several natural language processing (NLP) tasks has been enhanced thanks to the Transformer-based pre-trained language model BERT. We employ this concept to investigate a local publication database. Research papers are encoded and clustered to form a landscape view of the scientific topics, in which research is active. Authors working on similar topics can be identified by calculating the similarity between their papers. Based on this, we define a similarity metric between authors. Additionally we introduce the concept of self-similarity to indicate the topical variety of authors. Comment: Proc. of the Interdisciplinary Conference on Mechanics, Computers and Electrics (ICMECE 2022)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2306.09049 Zobrazit plný text záznamu View this record from Arxiv