Anaphora Resolution: Analysing the Impact on Mean Average Precision and Detecting Limitations of Automated Approaches

This article analyses the effect of anaphora resolution on information retrieval performance for systems with relevance ranking. It will be investigated if the Mean Average Precision of a retrieval system is improved after an intellectual replacement of all anaphors in a corpus with various texts. These texts mostly consist of news stories and fairy tales, thus covering two varying genres with different amounts of anaphors. A model retrieval system is developed using Lucene to measure the effects of anaphora resolution. Different queries are used and the rankings are analysed in order to show the changes induced by the anaphora resolution. In addition, approaches of automated anaphora resolution are considered. It turns out that the Mean Average Precision improves noticeably by 36% after the anaphora resolution. Thus, it is highly recommended to improve existing approaches of automated anaphora resolution in the future as current attempts do not yet yield satisfying results.