Zobrazeno 1 - 10
of 4 597
pro vyhledávání: '"Relation Extraction"'
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 11, Pp 2848-2871 (2024)
Information extraction is the foundation of knowledge graph construction, and relation extraction, as a key process and core step of information extraction, aims to locate entities from text data and recognize semantic links between entities. Therefo
Externí odkaz:
https://doaj.org/article/2285d428fa0d441f994476ebf334f793
Publikováno v:
Complex & Intelligent Systems, Vol 11, Iss 1, Pp 1-14 (2024)
Abstract Traditional education systems obscure the diverse interconnections inherent within subject knowledge, thus failing to meet the current demand for personalized and adaptive learning experiences. Recent advances have explored various relation
Externí odkaz:
https://doaj.org/article/0474f1454f9240e7b7aef32526943368
Publikováno v:
Complex & Intelligent Systems, Vol 11, Iss 1, Pp 1-12 (2024)
Abstract Document-level relation extraction (RE), which requires integrating and reasoning information to identify multiple possible relations among entities. However, previous research typically performed reasoning on heterogeneous graphs and set a
Externí odkaz:
https://doaj.org/article/d236cbfc53d34c67a13a168364e20e08
Publikováno v:
Complex & Intelligent Systems, Vol 11, Iss 1, Pp 1-15 (2024)
Abstract Zero-shot relation extraction (ZSRE) is essential for improving the understanding of natural language relations and enhancing the accuracy and efficiency of natural language processing methods in practical applications. However, the existing
Externí odkaz:
https://doaj.org/article/4a79ddabbf4d42db97b8a0879d67011a
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract In natural language processing, document-level relation extraction is a complex task that aims to predict the relationships among entities by capturing contextual interactions from an unstructured document. Existing graph- and transformer-ba
Externí odkaz:
https://doaj.org/article/7315ba94cb3945e7afe1cdf68276c714
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-28 (2024)
Abstract Background Relation extraction (RE) plays a crucial role in biomedical research as it is essential for uncovering complex semantic relationships between entities in textual data. Given the significance of RE in biomedical informatics and the
Externí odkaz:
https://doaj.org/article/bc1fc73af48342559367ee7c3b12b10f
Autor:
Wei Song, Zijiang Yang
Publikováno v:
AI, Vol 5, Iss 3, Pp 1709-1730 (2024)
Background: Distantly supervised relation extraction (DSRE) aims to identify semantic relations in large-scale texts automatically labeled via knowledge base alignment. It has garnered significant attention due to its high efficiency, but existing me
Externí odkaz:
https://doaj.org/article/c8e67e27db584941b1eeb0f189480a0c
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 9, Pp 2326-2336 (2024)
Relation extraction, as a key task in natural language processing, plays a significant role in deepening language understanding, constructing knowledge graphs, and optimizing information retrieval systems. However, traditional supervised learning met
Externí odkaz:
https://doaj.org/article/84f6e43c102c45628198bcbcbfb881df
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 6, Pp 7565-7575 (2024)
Abstract Prompt-tuning has emerged as a promising approach for improving the performance of classification tasks by converting them into masked language modeling problems through the insertion of text templates. Despite its considerable success, appl
Externí odkaz:
https://doaj.org/article/b47ca11454b34d428169cd975c0cb625
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Background Most Chinese joint entity and relation extraction tasks in medicine involve numerous nested entities, overlapping relations, and other challenging extraction issues. In response to these problems, some traditional methods decompos
Externí odkaz:
https://doaj.org/article/b408a8ab36db421c96e0f5becadccedc