Huawei's Noah's Ark Lab Co-organized ACM RecSys Conference to Support Research in Recommender Systems
Huawei, a leading global information and communications technology (ICT) solutions provider, co-organized the 7th ACM Conference on Recommender Systems 2013 (RecSys 2013) in Hong Kong. The conference was successfully concluded on October 16, 2013. Huawei's involvement in this conference led to a fruitful outcome. Besides presenting Huawei's research output in the areas of Big Data and recommender systems, the lab's participation in this conference has also strengthened its ties with academics and researchers from different organizations.
Recommender systems represent an important area of research in computer science. By analyzing huge amount of data, recommender systems automatically learn the correlations between user preferences and item characteristics, as well as the possible changes in the tastes or behaviour of the users under different situations, in order to generate more accurate and more personalized recommendations to end users.
Prof. Qiang Yang, head of Noah's Ark Lab, was the general co-chair of this conference. At the opening ceremony, Prof. Yang said that "it is the first time for this top conference in the area of recommender systems to be held in Asia. In the era of Big Data, the conference has special implications on both the academic and industrial communities. We wish the conference a great success!" The conference also invited Prof. Oren Etzioni (University of Washington), Dr. Dou Shen (Baidu Inc.), and Mr. Yan Mu (Baihe.com) to be the keynote speakers this year.
Noah's Ark Lab's deputy head Baofeng Zhang spoke at the opening ceremony. Chief scientist Dr. Hang Li spoke at the doctoral symposium and gave advice to PhD students attending the conference. In addition, principal researcher Wenyuan Dai presented Huawei's research effort in recommender systems at the industrial session. He analyzed the evolution of recommender systems in recent years, and introduced Huawei’s plan to develop next generation recommender systems that are tailored to the specific needs of different customers of Huawei, the technologies of which will greatly increase the accuracy of recommendations and at the same time reduce the amount of manual configuration required.
Noah's Ark Lab is also currently working on a few projects related to recommender systems, including:
1. Using recommendation technologies to generate personalized mobile apps recommendations to end users of HiCloud, the app store of Huawei.
2. Recommending tailored financial products to bank clients.
3. Developing a "Weibo Robot", which automatically analyzes content on the micro-blogging platform Weibo to recommend interesting content to followers.
4. Analysing user preferences and behaviour to develop the next generation mobile devices that will become partners of the end users, and will be able to make recommendations to the end users at any time.
While these projects are still at their early stages, they have already shown some promising results. For example, the mobile apps recommendation system has been able to increase the download rate in HiCloud by over 30%. The Weibo Robot has also gathered over 400 real followers on Weibo with very positive feedback on its recommendations (http://weibo.com/u/2867879661). The technologies developed in these projects will greatly increase Huawei’s capabilities in Big Data analysis and recommender systems, and put Huawei at a more competitive position in this age of Big Data.
The ACM RecSys is an internationally acclaimed conference series organized by the Association of Computing Machinery (ACM). Every year, the conference invites outstanding academics and researchers in the area of recommender systems to be keynote speakers. It also attracts academics and researchers to submit research papers, only a small amount of which will be accepted for presentation after a rigorous peer review process. The conference also holds the RecSys Challenge every year. In this competition, Internet or technology companies provide data and problem sets, and solicit innovative methods and techniques from researchers worldwide.
Noah's Ark Lab focuses on research related to Big Data, and is also putting much effort in the area of recommender systems. Noah's Ark Lab will continue to foster good relationship with researchers in academia and industry in the future, building long term collaborations and supporting research work in this area.
Recommender systems represent an important area of research in computer science. By analyzing huge amount of data, recommender systems automatically learn the correlations between user preferences and item characteristics, as well as the possible changes in the tastes or behaviour of the users under different situations, in order to generate more accurate and more personalized recommendations to end users.
Prof. Qiang Yang, head of Noah's Ark Lab, was the general co-chair of this conference. At the opening ceremony, Prof. Yang said that "it is the first time for this top conference in the area of recommender systems to be held in Asia. In the era of Big Data, the conference has special implications on both the academic and industrial communities. We wish the conference a great success!" The conference also invited Prof. Oren Etzioni (University of Washington), Dr. Dou Shen (Baidu Inc.), and Mr. Yan Mu (Baihe.com) to be the keynote speakers this year.
Noah's Ark Lab's deputy head Baofeng Zhang spoke at the opening ceremony. Chief scientist Dr. Hang Li spoke at the doctoral symposium and gave advice to PhD students attending the conference. In addition, principal researcher Wenyuan Dai presented Huawei's research effort in recommender systems at the industrial session. He analyzed the evolution of recommender systems in recent years, and introduced Huawei’s plan to develop next generation recommender systems that are tailored to the specific needs of different customers of Huawei, the technologies of which will greatly increase the accuracy of recommendations and at the same time reduce the amount of manual configuration required.
Noah's Ark Lab is also currently working on a few projects related to recommender systems, including:
1. Using recommendation technologies to generate personalized mobile apps recommendations to end users of HiCloud, the app store of Huawei.
2. Recommending tailored financial products to bank clients.
3. Developing a "Weibo Robot", which automatically analyzes content on the micro-blogging platform Weibo to recommend interesting content to followers.
4. Analysing user preferences and behaviour to develop the next generation mobile devices that will become partners of the end users, and will be able to make recommendations to the end users at any time.
While these projects are still at their early stages, they have already shown some promising results. For example, the mobile apps recommendation system has been able to increase the download rate in HiCloud by over 30%. The Weibo Robot has also gathered over 400 real followers on Weibo with very positive feedback on its recommendations (http://weibo.com/u/2867879661). The technologies developed in these projects will greatly increase Huawei’s capabilities in Big Data analysis and recommender systems, and put Huawei at a more competitive position in this age of Big Data.
The ACM RecSys is an internationally acclaimed conference series organized by the Association of Computing Machinery (ACM). Every year, the conference invites outstanding academics and researchers in the area of recommender systems to be keynote speakers. It also attracts academics and researchers to submit research papers, only a small amount of which will be accepted for presentation after a rigorous peer review process. The conference also holds the RecSys Challenge every year. In this competition, Internet or technology companies provide data and problem sets, and solicit innovative methods and techniques from researchers worldwide.
Noah's Ark Lab focuses on research related to Big Data, and is also putting much effort in the area of recommender systems. Noah's Ark Lab will continue to foster good relationship with researchers in academia and industry in the future, building long term collaborations and supporting research work in this area.
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