2009 | OriginalPaper | Chapter
Current Developments in Information Retrieval Evaluation
Author : Thomas Mandl
Published in: Advances in Information Retrieval
Publisher: Springer Berlin Heidelberg
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In the last decade, many evaluation results have been created within the evaluation initiatives like TREC, NTCIR and CLEF. The large amount of data available has led to substantial research on the validity of the evaluation procedure. An evaluation based on the Cranfield paradigm requires basically topics as descriptions of information needs, a document collection, systems to compare, human jurors to judge the documents retrieved by the systems against the information needs descriptions and some metric to compare the systems. For all these elements, there has been a scientific discussion. How many topics, systems, jurors and juror decisions are necessary to achieve valid results? How can the validity be measured? Which metrics are the most reliable ones and which metrics are appropriate from a user perspective? Examples from current CLEF experiments are used to illustrate some of the issues.
User based evaluations confront test users with the results of search systems and let them solve information tasks given in the experiment. In such a test setting, the performance of the user can be measured by observing the number of relevant documents he finds. This measure can be compared to a gold standard of relevance for the search topic to see if the perceived performance correlates with an objective notion of relevance defined by a juror. In addition, the user can be asked about his satisfaction with the search system and its results. In recent years, there has a growing concern on how well the results of batch and user studies correlate. When systems improve in a batch comparison and bring more relevant documents into the results list, do users get a benefit from this improvement? Are users more satisfied with better result lists and do better systems enable them to find more relevant documents? Some studies could not confirm this relation between system performance and user satisfaction.