Performance assessment of a semantic information retrieval system using stagnant and active images

Videos, images, graphics and text are the main multimedia data types. Generally, one document includes two or more data types because each data type enriches the meaning of document. For this reason, the documents become more complex for querying when compared with only text querying. To overcome this difficulty, some new information retrieval systems have been developed. In this study, an object action concept (OAC) based semantic information retrieval system for text and image data by using Fuzzy ontology was considered. Assessment of the performance of the retrieval systems is highly important. The purpose of this study is to assess the performance of an object action concept based semantic information retrieval system when using stagnant and active images. When considering the precision recall, precision and r_norm parameters, it is clear that the performance of the system for the stagnant images is higher than that for the active images.