WebMar 16, 2024 · The existing entity retrieval method used to retrieve the top 1000 candidate set of entities is BM25F-CA, which is the best-performing method for DBpediaV2 and provided by the creators. We use the Wiki2Vec embeddings trained on the 2024-07 dump by the authors of the original paper [ 9] to calculate the embedding reranking score. WebGraph-Embedding Empowered Entity Retrieval Emma J. Gerritse, Faegheh Hasibi, Arjen P. de Vries Journal-ref: Advances in Information Retrieval. ECIR 2024. Lecture Notes in Computer Science, vol 12035. Springer, Subjects: Information Retrieval (cs.IR); Computation and Language (cs.CL) [23] arXiv:2005.02844 [ pdf, other]
Knowledge Graph Embedding Based on Multi-View Clustering …
WebMentioning: 10 - In this research, we improve upon the current state of the art in entity retrieval by re-ranking the result list using graph embeddings. The paper shows that graph embeddings are useful for entity-oriented search tasks. We demonstrate empirically that encoding information from the knowledge graph into (graph) embeddings contributes to … WebGraph-Embedding Empowered Entity Retrieval. informagi/GEEER • 6 May 2024. In this research, we improve upon the current state of the art in entity retrieval by re-ranking … dm brazilian jiu-jitsu academy
Knowledge Graph Embedding Based on Multi-View Clustering Framework ...
WebApr 12, 2024 · Graph-embedding learning is the foundation of complex information network analysis, aiming to represent nodes in a graph network as low-dimensional dense real-valued vectors for the application in practical analysis tasks. In recent years, the study of graph network representation learning has received increasing attention from … WebAbstract—Knowledge representation is one of the critical problems in knowledge engineering and artificial intelli- gence, while knowledge embedding as a knowledge rep- resentation methodology indicates entities and relations in knowledge graph as low-dimensional, continuous vectors. WebApr 30, 2024 · Our dataset involves exploring large knowledge graphs (KG) to retrieve abundant knowledge of various types of main entities, which makes the current graph-to-sequence models severely suffered... dm brazilian love