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Knowledge enhanced sequential entity linking

http://dbgroup.cs.tsinghua.edu.cn/wangjy/papers/TKDE14-entitylinking.pdf

Knowledge-Enhanced Graph Neural Networks for …

WebSep 26, 2024 · Entity Linking Meets Deep Learning: Techniques and Solutions Wei Shen, Yuhan Li, Yinan Liu, Jiawei Han, Jianyong Wang, Xiaojie Yuan Entity linking (EL) is the process of linking entity mentions appearing in web text with their corresponding entities in a knowledge base. WebFew-shot sequence labeling is a general problem formulation for many natural language understanding tasks in data-scarcity scenarios, which require models to generalize to new types via only a few labeled examples. Recent advances mostly adopt metric-based meta-learning and thus face the challenges of modeling the miscellaneous Other prototype and … reddick to ocala https://korperharmonie.com

GFE: General Knowledge Enhanced Framework for Explainable Sequential …

WebApr 14, 2024 · In this paper, we propose a Knowledge graph enhanced Recommendation with Context awareness and Contrastive learning (KRec-C2) to overcome the issue. Specifically, we design an category-level ... WebIt is vital for sequential recommendation to provide accurate and explainable results for user, which can help them make better decisions. In this paper, we develop a General Knowledge Enhanced Framework for Explainable Sequential Recommendation (GFE) to capture user’s fine-grained preferences and dynamic preferences evolution. WebApr 14, 2024 · Conditional phrases provide fine-grained domain knowledge in various industries, including medicine, manufacturing, and others. Most existing knowledge extraction research focuses on mining triplets with entities and relations and treats that triplet knowledge as plain facts without considering the conditional modality of such … reddick twitter

Accepted papers EMNLP 2024

Category:GFE: General Knowledge Enhanced Framework for Explainable Sequential …

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Knowledge enhanced sequential entity linking

Applied Sciences Free Full-Text Conditional Knowledge …

WebOct 20, 2024 · On one hand, we propose a simple but effective coarse-to-fine unsupervised knowledge base (KB) extraction approach to improve the quality of KB, through which we … WebApr 7, 2024 · Abstract Injecting external domain-specific knowledge (e.g., UMLS) into pretrained language models (LMs) advances their capability to handle specialised in-domain tasks such as biomedical entity linking (BEL). However, such abundant expert knowledge is available only for a handful of languages (e.g., English).

Knowledge enhanced sequential entity linking

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Web4 rows · 1. We propose a novel EL model, Knowledge Enhanced Sequential Entity Linking (KESEL), which ... WebJul 18, 2024 · Knowledge Enhanced Sequential Entity Linking Authors: Yu Liu Shi Wang Chinese Academy of Sciences Kangli Zi Jicun Li 20+ million members 135+ million …

WebApr 14, 2024 · Entity disambiguation, also known as entity linking, is the task of mapping mentions in text to the corresponding entities in a given knowledge base, e.g., Wikipedia. WebJul 7, 2024 · Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions. IEEE Transactions on Knowledge and Data Engineering , Vol. 27 (2015), 443--460. Cees GM Snoek, Marcel Worring, and Arnold WM Smeulders. 2005. Early Versus Late Fusion in Semantic Video Analysis.

WebEntity Linking (EL) is the task of mapping mentions in texts to the corresponding entities in knowledge bases. Existing studies mostly focus on joint disambiguation based on the … WebDec 8, 2024 · Entity linking aims to establish a link between entity mentions in a document and the corresponding entities in knowledge graphs (KGs). Previous work has shown the …

WebEntity Linking and Named Entity Recognition, and encourage further studies on high-performance EL systems for scenarios in which only a small amount of labeled data is …

WebApr 14, 2024 · A knowledge graph is a large-scale semantic network that generates new knowledge by acquiring information and integrating it into a knowledge base and then … known food in the philippinesWebFeb 21, 2024 · Meta relational learning Approaches to Knowledge Graph Completion 64 of 96. 66. 1. Embedding-based (ranking) methods For the link prediction KGC task, i.e. for the KGC task with triples (h, r, t) with h or t missing: learn embedding vectors based on existing triples: during test, the missing h or t entity is predicted from the existing set E of ... known food for mexicoWebEntity Linking and Entity Disambiguation 1. Summary. Surveys and Analysis. Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions (TKDE 2014) [] 🌟Neural Entity Linking: A Survey of Models based on Deep Learning (2024) []a survey of state-of-the-art neural entity linking models reddick tree service