Multi-Stakeholder Recommendation: Applications and Challenges

نویسنده

  • Yong Zheng
چکیده

Recommender systems have been successfully applied to assist decision making by producing a list of item recommendations tailored to user preferences. Traditional recommender systems only focus on optimizing the utility of the end users who are the receiver of the recommendations. By contrast, multi-stakeholder recommendation aŠempts to generate recommendations that satisfy the needs of both the end users and other parties or stakeholders. Œis paper provides an overview and discussion about the multi-stakeholder recommendations from the perspective of practical applications, available data sets, corresponding research challenges and potential solutions.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Multi-Objective Learning to re-Rank Approach to Optimize Online Marketplaces for Multiple Stakeholders

Multi-objective recommender systems address the difficult task of recommending items that are relevant to multiple, possibly conflicting, criteria. However these systems aremost o‰en designed to address the objective of one single stakeholder, typically, in online commerce, the consumers whose input and purchasing decisions ultimately determine the success of the recommendation systems. In this...

متن کامل

Towards Multi-Stakeholder Utility Evaluation of Recommender Systems

A core value in recommender systems is personalization, the idea that the recommendations produced are those that match the user’s preferences. However, in many real-world recommendation contexts, the concerns of additional stakeholders may come into play, such as the producers of items or those of the system owner. Some researchers have examined special cases of such concerns, for example, in ...

متن کامل

Patterns of Multistakeholder Recommendation

Recommender systems are personalized information systems. However, in many settings, the end-user of the recommendations is not the only party whose needs must be represented in recommendation generation. Incorporating this insight gives rise to the notion of multistakeholder recommendation, in which the interests of multiple parties are represented in recommendation algorithms and evaluation. ...

متن کامل

User Preference Learning with Multiple Information Fusion for Restaurant Recommendation

If properly analyzed, the multi-aspect rating data could be a source of rich intelligence for providing personalized restaurant recommendations. Indeed, while recommender systems have been studied for various applications and many recommendation techniques have been developed for general or specific recommendation tasks, there are few studies for restaurant recommendation by addressing the uniq...

متن کامل

System For Product Recommendation In E-Commerce Applications

Recommendation technology, is an important method for information filtering in E-Commerce applications, and can effectively reduce information overload in Internet. It narrows down the choice of products from a large number of product offerings. With increase in the number of E-commerce users and products, the original recommendation algorithms and systems face many challenges namely in modelin...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1707.08913  شماره 

صفحات  -

تاریخ انتشار 2017