no code implementations • EMNLP 2021 • Anna Tigunova, Paramita Mirza, Andrew Yates, Gerhard Weikum
Automatically extracting interpersonal relationships of conversation interlocutors can enrich personal knowledge bases to enhance personalized search, recommenders and chatbots.
no code implementations • EMNLP 2020 • Anna Tigunova, Andrew Yates, Paramita Mirza, Gerhard Weikum
Personal knowledge about users{'} professions, hobbies, favorite food, and travel preferences, among others, is a valuable asset for individualized AI, such as recommenders or chatbots.
no code implementations • 2 Nov 2023 • Ghazaleh Haratinezhad Torbati, Anna Tigunova, Andrew Yates, Gerhard Weikum
Recommender systems are most successful for popular items and users with ample interactions (likes, ratings etc.).
no code implementations • LREC 2020 • Anna Tigunova, Paramita Mirza, Andrew Yates, Gerhard Weikum
To the best of our knowledge, RedDust is the first annotated language resource about Reddit users at large scale.
1 code implementation • 24 Apr 2019 • Anna Tigunova, Andrew Yates, Paramita Mirza, Gerhard Weikum
Open-domain dialogue agents must be able to converse about many topics while incorporating knowledge about the user into the conversation.