Keynotes
Title:
Conversation in recommendation – opportunities and challenges
Abstract: Most current approaches to recommendation operate as a black box without explicit user interaction. A new form of interactive recommendation - conversational recommendation – is emerging in both industry and academia. In order to make recommendations, the system needs to interact with the user, through conversation, in order to determine the need of the user and to make good choices. In this talk, I will discuss what a conversational recommender can do beyond traditional systems, the possible approaches to be used, as well as the challenges.
Abstract: Most current approaches to recommendation operate as a black box without explicit user interaction. A new form of interactive recommendation - conversational recommendation – is emerging in both industry and academia. In order to make recommendations, the system needs to interact with the user, through conversation, in order to determine the need of the user and to make good choices. In this talk, I will discuss what a conversational recommender can do beyond traditional systems, the possible approaches to be used, as well as the challenges.
Title:
Personalized Language Modeling, from Prediction to Generation and Justification
Abstract: I'll give a historical perspective on the use of NLP for recommendation, with a particular focus on personalized language generation. Examples include models for question answering, text and recipe generation, and interpretability. By personalizing these models, we are better able to adapt to both the preferences and the linguistic nuances of individuals.
Abstract: I'll give a historical perspective on the use of NLP for recommendation, with a particular focus on personalized language generation. Examples include models for question answering, text and recipe generation, and interpretability. By personalizing these models, we are better able to adapt to both the preferences and the linguistic nuances of individuals.
