Titlebook: Information Retrieval; 28th China Conferenc Yi Chang,Xiaofei Zhu Conference proceedings 2023 Springer Nature Switzerland AG 2023 artificial

烤問(wèn)

書(shū)目名稱Information Retrieval影響因子(影響力)




書(shū)目名稱Information Retrieval影響因子(影響力)學(xué)科排名




書(shū)目名稱Information Retrieval網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Information Retrieval網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Information Retrieval被引頻次




書(shū)目名稱Information Retrieval被引頻次學(xué)科排名




書(shū)目名稱Information Retrieval年度引用




書(shū)目名稱Information Retrieval年度引用學(xué)科排名




書(shū)目名稱Information Retrieval讀者反饋




書(shū)目名稱Information Retrieval讀者反饋學(xué)科排名

FER

,ID-Agnostic User Behavior Pre-training for?Sequential Recommendation,ser behavior sequences based on item IDs. However, this kind of approach highly relies on user-item interaction data and neglects the attribute- or characteristic-level correlations among similar items preferred by a user. In light of these issues, we propose ., which stands for .-.gnostic User Beha

拋棄的貨物

Pulmonary-Veins

Frenetic

inconceivable

,InDNI: An Infection Time Independent Method for?Diffusion Network Inference,l role it plays in some real applications, such as rumor-spread forecasting and epidemic controlling. Most existing methods tackle the task with exact node infection time. However, collecting infection time information is time-consuming and labor-intensive, especially when information flows are huge

分開(kāi)

Bravura

,A Learnable Graph Convolutional Neural Network Model for?Relation Extraction,ncies relevant to named entities. Recently, graph convolutional neural networks have shown great potential in supporting this task, wherein dependency trees are usually adopted to learn semantic dependencies between entities. However, the requirement of external toolkits to parse sentences poses a p

大酒杯

使迷醉