Paper: Information Retrieval Capable of Visualization and High Precision

ACL ID I05-2024
Title Information Retrieval Capable of Visualization and High Precision
Venue International Joint Conference on Natural Language Processing
Session poster-demo-tutorial
Year 2005
Authors

We present a neural-network based self- organizing approach that enables vi- sualization of the information retrieval while at the same time improving its precision. In computer experiments, two-dimensional documentary maps in which queries and documents were mapped in topological order accord- ing to their similarities were created. The ranking of the results retrieved us- ing the maps was better than that of the results obtained using a conven- tional TFIDF method. Furthermore, the precision of the proposed method was much higher than that of the conven- tional TFIDF method when the process was focused on retrieving highly rel- evant documents, suggesting that the proposed method might be especially suited to information retrieval tasks in which precision is more critical than re- call.