Titlebook: Database Systems for Advanced Applications; 27th International C Arnab Bhattacharya,Janice Lee Mong Li,Rage Uday Ki Conference proceedings

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書目名稱Database Systems for Advanced Applications影響因子(影響力)




書目名稱Database Systems for Advanced Applications影響因子(影響力)學(xué)科排名




書目名稱Database Systems for Advanced Applications網(wǎng)絡(luò)公開度




書目名稱Database Systems for Advanced Applications網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Database Systems for Advanced Applications被引頻次




書目名稱Database Systems for Advanced Applications被引頻次學(xué)科排名




書目名稱Database Systems for Advanced Applications年度引用




書目名稱Database Systems for Advanced Applications年度引用學(xué)科排名




書目名稱Database Systems for Advanced Applications讀者反饋




書目名稱Database Systems for Advanced Applications讀者反饋學(xué)科排名

不可知論

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

innate

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

collagen

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

萬靈丹

prolate

外觀

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 .