• WWW 23

    The Web Conference. The Web Conference is the premier conference focused on understanding the current state and the evolution of the Web through the lens of computer science, computational social science, economics, policy, and many other disciplines. The Web Conference (formerly www conference) is a yearly interna ...

    Austin, Texas, USA,

    摘要截止日期: October 6, 2022

    正文截止日期: October 13, 2022

  • AAAI 23

    the American Association for Artificial Intelligence. Founded in 1979, the Association for the Advancement of Artificial Intelligence (AAAI) (formerly the American Association for Artificial Intelligence) is a nonprofit scientific society devoted to advancing the scientific understanding of the mechanisms underlying thought and intelligent behavior and ...

    Washington, DC, USA,

    摘要截止日期: August 8, 2022

    正文截止日期: August 15, 2022

  • SIGIR2022

    the Association for Computing Machinery’s Special Interest Group on Information Retrieval. SIGIR is the Association for Computing Machinery’s Special Interest Group on Information Retrieval. Since 1963, we have promoted research, development and education in the area of search and other information access technologies. ...

    Madrid, Spain, July 11th to 15th, 2022

    摘要截止日期: January 21, 2022

    正文截止日期: January 28, 2022

  • WSDM2023

    ACM International Conference on Web Search and Data Mining. WSDM is a highly selective conference that includes invited talks, as well as refereed full papers. WSDM publishes original, high-quality papers related to search and data mining on the Web and the Social Web, with an emphasis on practical yet principled novel models of search and data mining, algor ...

    TBD,

    摘要截止日期: TBD

    正文截止日期:

  • IJCAI2022

    The International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence is a non-profit corporation founded in California, in 1969 for scientific and educational purposes, including dissemination of information on Artificial Intelligence at conferences in which cutting-edge scientific results are presented and t ...

    Austria, July 23-29, 2022

    摘要截止日期: January 7, 2022

    正文截止日期: January 14, 2022


Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability 2019-11-22 15:27:14
Recent years have witnessed growing interests in developing deep models for incremental learning. However, existing approaches often utilize the fixed structure and online backpropagation for deep model optimization, which is difficult to be implemented for incremental data scenarios. Indeed, for st... || 增量学习; 在线学习; fisher information matrix;对之前学好的模型参数建模,从而保存之前的信息; || Yang Yang; Hui Xiong...

A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction 2019-11-21 09:32:58
The understanding of job mobility can benefit talent management operations in a number of ways, such as talent recruitment, talent development, and talent retention. While there is extensive literature showing the predictability of the organization-level job mobility patterns (e.g., in terms of the ... ; || Qingxin Meng; Hui Xiong...

Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling 2019-11-15 21:11:53
Sequential recommendation task aims to predict user preference over items in the future given user historical behaviors. The order of user behaviors implies that there are resourceful sequential patterns embedded in the behavior history which reveal the underlying dynamics of user interests. Various... || Sequential Recommendation, Collaborative Filtering, Co-Attention; GRU; || Jiarui Qin; Kan Ren...

WhyWe Go Where We Go: Profiling User Decisions on Choosing POIs 2019-11-14 10:44:06
While Point-of-Interest (POI) recommendation has been a popular topic of study for some time, little progress has been made for understanding why and how people make their decisions for the selection of POIs. To this end, in this paper, we propose a user decision profiling framework, named PROUD, wh... || scalar projection; 一个利用scalar projection做的attention方法; || Renjun Hu; Xinjiang Lu...

Sequential Scenario-Specific Meta Learner for Online Recommendation 2019-11-07 20:13:24
Cold-start problems are long-standing challenges for practical recommendations. Most existing recommendation algorithms rely on extensive observed data and are brittle to recommendation scenarios with few interactions. This paper addresses such problems using few-shot learning and meta learning. Our... || few-shot learning; meta learning; LSTM; early-stop policy; learning rate;; || Zhengxiao Du...

Session-based recommendations with recurrent neural networks 2019-11-05 20:02:13
We apply recurrent neural networks (RNN) on a new domain, namely recommender systems. Real-life recommender systems often face the problem of having to base recommendations only on short session-based data (e.g. a small sportsware website) instead of long user histories (as in the case of Netflix). ... || GRU4Rec-basic; || Bal´azs Hidasi...

Streaming Session-based Recommendation 2019-11-05 09:23:30
Session-based Recommendation (SR) is the task of recommending the next item based on previously recorded user interactions. In this work, we study SR in a practical streaming scenario, namely Streaming Session-based Recommendation (SSR), which is a more challenging task due to (1) the uncertainty of... || Session Recommendation; Streaming Recommendation; Attention Model; Matrix Factorization; GRU;paired sample t-test; 配对样本t检验; || Lei Guo...