Model-based Approaches for Independence-Enhanced RecommendationToshihiro Kamishima
Model-based Approaches for Independence-Enhanced Recommendation
IEEE International Workshop on Privacy Aspects of Data Mining (PADM), in conjunction with ICDM2016
Article @ Official Site: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2016.0127
Workshop Homepage: http://pddm16.eurecat.org/
Abstract:
This paper studies a new approach to enhance recommendation independence. Such approaches are useful in ensuring adherence to laws and regulations, fair treatment of content providers, and exclusion of unwanted information. For example, recommendations that match an employer with a job applicant should not be based on socially sensitive information, such as gender or race, from the perspective of social fairness. An algorithm that could exclude the influence of such sensitive information would be useful in this case. We previously gave a formal definition of recommendation independence and proposed a method adopting a regularizer that imposes such an independence constraint. As no other options than this regularization approach have been put forward, we here propose a new model-based approach, which is based on a generative model that satisfies the constraint of recommendation independence. We apply this approach to a latent class model and empirically show that the model-based approach can enhance recommendation independence. Recommendation algorithms based on generative models, such as topic models, are important, because they have a flexible functionality that enables them to incorporate a wide variety of information types. Our new model-based approach will broaden the applications of independence-enhanced recommendation by integrating the functionality of generative models.
Yokogawa, globally recognized leader in a number of process control fields, has authored an e-book which provides useful insight into how operators of combustion based equipment and systems can improve efficiency and enhance safety by employing modern technology.
TEDx Manchester: AI & The Future of WorkVolker Hirsch
TEDx Manchester talk on artificial intelligence (AI) and how the ascent of AI and robotics impacts our future work environments.
The video of the talk is now also available here: https://youtu.be/dRw4d2Si8LA
Model-based Approaches for Independence-Enhanced RecommendationToshihiro Kamishima
Model-based Approaches for Independence-Enhanced Recommendation
IEEE International Workshop on Privacy Aspects of Data Mining (PADM), in conjunction with ICDM2016
Article @ Official Site: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2016.0127
Workshop Homepage: http://pddm16.eurecat.org/
Abstract:
This paper studies a new approach to enhance recommendation independence. Such approaches are useful in ensuring adherence to laws and regulations, fair treatment of content providers, and exclusion of unwanted information. For example, recommendations that match an employer with a job applicant should not be based on socially sensitive information, such as gender or race, from the perspective of social fairness. An algorithm that could exclude the influence of such sensitive information would be useful in this case. We previously gave a formal definition of recommendation independence and proposed a method adopting a regularizer that imposes such an independence constraint. As no other options than this regularization approach have been put forward, we here propose a new model-based approach, which is based on a generative model that satisfies the constraint of recommendation independence. We apply this approach to a latent class model and empirically show that the model-based approach can enhance recommendation independence. Recommendation algorithms based on generative models, such as topic models, are important, because they have a flexible functionality that enables them to incorporate a wide variety of information types. Our new model-based approach will broaden the applications of independence-enhanced recommendation by integrating the functionality of generative models.
Yokogawa, globally recognized leader in a number of process control fields, has authored an e-book which provides useful insight into how operators of combustion based equipment and systems can improve efficiency and enhance safety by employing modern technology.
TEDx Manchester: AI & The Future of WorkVolker Hirsch
TEDx Manchester talk on artificial intelligence (AI) and how the ascent of AI and robotics impacts our future work environments.
The video of the talk is now also available here: https://youtu.be/dRw4d2Si8LA
Lika products catalogue for wind generator industry - Japanese versionLika Electronic
Lika Electronic confirms its continued commitment to developing position measurement & control systems technologically advanced and tailored to solve even the specialised and individual requirements of increasingly fragmented and dynamic markets, offering a new range of linear and rotary encoders specifically designed for installation in safety and feedback control systems of wind turbines. This catalogue shows the wide range of rotary and linear, optical and magnetic, incremental and absolute singleturn & multiturn encoders that Lika Electronic, thanks to its solid and proven experience in wind power industry both on and offshore, has especially developed to tackle critical tasks and harsh conditions affecting each specific application in wind generators. They do not only encompass high quality, heavy-duty sturdiness, outstanding dependability and absolute safety which are the trademark of Lika Electronic, but also keep up with trends and even anticipate the high-level requirements of a sector where technological advancement is continuously and rapidly evolving.
Lika products catalogue for wind generator industry - Japanese versionLika Electronic
Lika Electronic confirms its continued commitment to developing position measurement & control systems technologically advanced and tailored to solve even the specialised and individual requirements of increasingly fragmented and dynamic markets, offering a new range of linear and rotary encoders specifically designed for installation in safety and feedback control systems of wind turbines. This catalogue shows the wide range of rotary and linear, optical and magnetic, incremental and absolute singleturn & multiturn encoders that Lika Electronic, thanks to its solid and proven experience in wind power industry both on and offshore, has especially developed to tackle critical tasks and harsh conditions affecting each specific application in wind generators. They do not only encompass high quality, heavy-duty sturdiness, outstanding dependability and absolute safety which are the trademark of Lika Electronic, but also keep up with trends and even anticipate the high-level requirements of a sector where technological advancement is continuously and rapidly evolving.