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This is the unspecified version of the paper.This version of the publication may differ from the final published version. Permanent repository link Andy MacFarlane Department of Information Science, City University London, UK Pauline Rafferty Department of Information Studies, University of Aberystwyth, Wales AbstractAlthough known item searching for music can be dealt with by searching metadata using existing text search techniques, human subjectivity and variability within the music itself make it very difficult to search for unknown items. This paper examines these problems within the context of text retrieval and music information retrieval. The focus is on ascertaining a relationship between music relevance criteria and those relating to relevance judgements in text retrieval. A data-rich collection of relevance judgements by creative professionals searching for unknown musical items to accompany moving images using real world queries is analysed. The participants in our observations are found to take a socio-cognitive approach and use a range of content and context based criteria. These criteria correlate strongly with those arising from previous text retrieval studies despite the many differences between music and text in their actual content.

Creative professionals search for music to accompany moving images in films, advertising, television. Some larger music rights holders (record companies and music publishers) organise their catalogues to allow online searching. These digital libraries are organised by various subjective musical facets as well as by artist and title metadata. A facet analysis of a number of queries is discussed in relation to the organisation of the music in these bespoke search engines. Subjective facets such as Mood and Genre are found to be highly important in query formation. These findings are discussed in relation to disintermediation of this process. It is suggested that there are a number of barriers to this, both in terms of classification approaches and also commercial / legal factors.

This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractThis study explored how the expression of search facets and relevance feedback by users was related to search success in interactive and automatic query expansion in the course of the search process. Search success was measured both in the number of relevant documents retrieved and relevance scores of these items based on a four point scaling. Research design consisted of 26 users searching for four TREC topics in Okapi IR system, half using interactive and half automatic query expansion based on RF. The search logs were recorded, and the users filled in a questionnaire for each topic concerning various features of searching. The results showed that the exhaustivity of the query was the most significant predictor of search success, and that interactive expansion led to better search success than automatic one.2

This is the accepted version of the paper.This version of the publication may differ from the final published version. The progress of parallel computing in Information Retrieval (IR) is reviewed. In particular we stress the importance of the motivation in using parallel computing for Text Retrieval. We analyse parallel IR systems using a classification due to Rasmussen [1] and describe some parallel IR systems. We give a description of the retrieval models used in parallel Information PermanentProcessing.. We describe areas of research which we believe are needed.