Balancing utility and fairness in the search results is an important and challenging problem for the IR community. The FairWeb-2 Task of NTCIR-18 aims to tackle this using three main search topics: movies, researchers and YouTube videos. This paper presents the approach employed by the AMS42 team as part of the FairWeb-2 Task of NTCIR-18. The AMS42 team submitted 5 runs. First, we focus on retrieving documents which are relevant to the given queries. Next, we employ two fairness approaches. One of which makes use of estimated sensitive attribute values to balance relevance and fairness in the retrieved results, and another which relies on the model's semantic understanding of sensitive attribute values derived from the document content. Finally, we discuss the challenges identified while working on the FairWeb-2 Task.
Rus et al. (2025) studied this question.