Titlebook: Computer Supported Cooperative Work and Social Computing; 16th CCF Conference, Yuqing Sun,Tun Lu,Liping Gao Conference proceedings 2022 Spr

阻止

瑪瑙

The Contemporary Russian Economyector-wise in both implicit and explicit ways, but also learn both low-order and high-order feature interactions. xDeepFM can effectively enhance recommendation accuracy. Finally, the recommendation model is embedded in the system for testing. Evaluate on the public dataset of DiDi, we compare diffe

反饋

JIBE

How Do Scholars and Academics Differ?ion, which requires prior knowledge to set metapaths in advance. This paper proposes a novel random-walk-based heterogeneous attention network (RHAN) for community detection on heterogeneous networks. Random walk is used to generate the neighbor nodes set of nodes, and heterogeneous information is c

GROG

FLAG

Computer Supported Cooperative Work and Social Computing16th CCF Conference,

IVORY

Joint Embedding Multiple Feature and Rule for Paper Recommendations papers are recommended according to the relatedness between user interests and paper embeddings. We conduct experiments on the ACM academic paper dataset. The results show that our model outperforms baseline methods on personalized recommendation. We also analyze the influence of model structure a

混雜人

LVAD360

Deep Bug Triage Model Based on Multi-head Self-attention Mechanismport, and further quantifies the influence of fixers with similar activities on bug triage through fixer sequence. We conducted texts on four open source software projects. We can get the MSDBT has clear strength over the previous model in recall index.

異教徒

Taxi Pick-Up Area Recommendation via Integrating Spatio-Temporal Contexts into XDeepFMector-wise in both implicit and explicit ways, but also learn both low-order and high-order feature interactions. xDeepFM can effectively enhance recommendation accuracy. Finally, the recommendation model is embedded in the system for testing. Evaluate on the public dataset of DiDi, we compare diffe