interleukins
发表于 2025-3-21 18:25:48
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不可知论
发表于 2025-3-21 21:13:00
Information Networks Based Multi-semantic Data Embedding for Entity Resolutions. Recently, deep learning techniques have been substantially applied to entity resolution. We focus on entity resolution with graph based multi-semantic data embedding. In ER, data with attributes cannot be well represented by common word embeddings from natural language processing. In this work, d
Insatiable
发表于 2025-3-22 02:40:11
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innate
发表于 2025-3-22 06:17:02
Empowering Transformer with Hybrid Matching Knowledge for Entity Matchingoken-level pairwise interactions within the input sequence. In this paper, we propose a novel entity matching framework named GTA. GTA enhances Transformer for relational data representation by injecting additional hybrid matching knowledge. The hybrid matching knowledge is obtained via graph contra
regale
发表于 2025-3-22 12:21:38
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collagen
发表于 2025-3-22 15:39:15
Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks challenges of the task lie in how to comprehend the story context sufficiently and handle the implicit knowledge behind story clues effectively, which are still under-explored by previous work. In this paper, we propose a Story Heterogeneous Graph Network (SHGN) to explicitly model both the informa
collagen
发表于 2025-3-22 18:16:02
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万灵丹
发表于 2025-3-22 23:44:44
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prolate
发表于 2025-3-23 02:13:30
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外观
发表于 2025-3-23 06:23:31
Aligning Internal Regularity and External Influence of Multi-granularity for Temporal Knowledge Grapthe internal and external influence at either element level or fact level. However, the multi-granularity information is essential for TKG modeling and the connection in between is also under-explored. In this paper, we propose the method that .ligning-internal .egularity and external .nfluence of .