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Joint Modeling and Optimization of Search and Recommendation
We list a number of future directions for this line of research that can potentially lead to development of state-of-the-art search and recommendation models.
Target Apps Selection: Towards a Unified Search Framework for Mobile Devices
As a consequence, users are getting engaged with the mobile apps and frequently search for an information need in their apps.
Towards Theoretical Understanding of Weak Supervision for Information Retrieval
We briefly review a set of our recent theoretical findings that shed light on learning from weakly supervised data, and provide guidelines on how train learning to rank models with weak supervision.
Current Challenges and Visions in Music Recommender Systems Research
Music recommender systems (MRS) have experienced a boom in recent years, thanks to the emergence and success of online streaming services, which nowadays make available almost all music in the world at the user's fingertip.
Neural Ranking Models with Multiple Document Fields
However, such models have often been based on one field of the document, for example considering document title only or document body only.
