A Survey on Session-based Recommender Systems <s> Attention in the Research Community <s> We believe that Deep Learning is one of the next big things in Recommendation Systems technology. The past few years have seen the tremendous success of deep neural networks in a number of complex tasks such as computer vision, natural language processing and speech recognition. Despite this, only little work has been published on Deep Learning methods for Recommender Systems. Notable recent application areas are music recommendation, news recommendation, and session-based recommendation. The aim of the workshop is to encourage the application of Deep Learning techniques in Recommender Systems, to promote research in deep learning methods for Recommender Systems, and to bring together researchers from the Recommender Systems and Deep Learning communities. <s> BIB001 </s> A Survey on Session-based Recommender Systems <s> Attention in the Research Community <s> Deep Learning is one of the next big things in Recommendation Systems technology. The past few years have seen the tremendous success of deep neural networks in a number of complex machine learning tasks such as computer vision, natural language processing and speech recognition. After its relatively slow uptake by the recommender systems community, deep learning for recommender systems became widely popular in 2016. We believe that a tutorial on the topic of deep learning will do its share to further popularize the topic. Notable recent application areas are music recommendation, news recommendation, and session-based recommendation. The aim of the tutorial is to encourage the application of Deep Learning techniques in Recommender Systems, to further promote research in deep learning methods for Recommender Systems. <s> BIB002
Today, work related to SBRS appears widely in several top conferences on data mining like KDD, CIKM and WSDM, on machine learning and artificial intelligence like AAAI, IJCAI and ECML, and on their applications like Recsys, WWW and SIGIR. In addition to the publications on general RS topics that were scattered in a variety of top conferences, there are also special events which particularly focus on SBRS. For example, there is a separate session called SBRS in ACM RecSys 2017 2 and related keynote speeches on SBRS 3 . SBRS also accounts for a large portion of a workshop called deep learning in RS BIB001 held in RecSys 2016 and another workshop  together with a tutorial BIB002 on the same topic in the same conference in 2017.