106 citations · 273 across the 31 of their papers we have counts for
21 papers · 1 filter
Recommending Target Actions Outside Sessions in the Data-poor Insurance Domain
Simone Borg Bruun, Christina Lioma, Maria Maistro
Providing personalized recommendations for insurance products is particularly challenging due to the intrinsic and distinctive features of the insurance domain. First, unlike more…
Evaluation Measures of Individual Item Fairness for Recommender Systems: A Critical Study
Theresia Veronika Rampisela, Maria Maistro, Tuukka Ruotsalo +1
Fairness is an emerging and challenging topic in recommender systems. In recent years, various ways of evaluating and therefore improving fairness have emerged. In this study, we e…
Principled Multi-Aspect Evaluation Measures of Rankings
Maria Maistro, Lucas Chaves Lima, Jakob Grue Simonsen +1
Information Retrieval evaluation has traditionally focused on defining principled ways of assessing the relevance of a ranked list of documents with respect to a query. Several met…
Learning Recommendations from User Actions in the Item-poor Insurance Domain
Simone Borg Bruun, Maria Maistro, Christina Lioma
While personalised recommendations are successful in domains like retail, where large volumes of user feedback on items are available, the generation of automatic recommendations i…
Unsupervised Multi-Index Semantic Hashing
Christian Hansen, Casper Hansen, Jakob Grue Simonsen +2
Semantic hashing represents documents as compact binary vectors (hash codes) and allows both efficient and effective similarity search in large-scale information retrieval. The sta…
Projected Hamming Dissimilarity for Bit-Level Importance Coding in Collaborative Filtering
Christian Hansen, Casper Hansen, Jakob Grue Simonsen +1
When reasoning about tasks that involve large amounts of data, a common approach is to represent data items as objects in the Hamming space where operations can be done efficiently…