Explainable Information Retrieval: A Survey

Explainable information retrieval is an emerging research area aiming to make transparent and trustworthy information retrieval systems. Given the increasing use of complex machine learning models in search systems, explainability is essential in building and auditing responsible information retrieval models. This survey fills a vital gap in the otherwise topically diverse literature of explainable information retrieval. It categorizes and discusses recent explainability methods developed for different application domains in information retrieval, providing a common framework and unifying perspectives. In addition, it reflects on the common concern of evaluating explanations and highlights open challenges and opportunities.Comment: 35 pages, 10 figures. Under revie

Music, movies and meaning: communication in film-markers' search for pre-existing music, and the implications for music information retrieval

While the use of music to accompany moving images is widespread, the information behaviour, communicative practice and decision making by creative professionals within this area of the music industry is an under-researched area. This investigation discusses the use of music in films and advertising focusing on communication and meaning of the music and introduces a reflexive communication model. The model is discussed in relation to interviews with a sample of music professionals who search for and use music for their work. Key factors in this process include stakeholders, briefs, product knowledge and relevance. Searching by both content and context is important, although the final decision when matching music to picture is partly intuitive and determined by a range of stakeholders