This paper presents the framework of our WWW image indexing and searching system. The semantics of an image are obtained by analyzing its associated texts. During the processing, stopword-removing and term-stemming algorithms are applied in order to reduce the noises and highlight the semantic concepts of images. In our solution, the semantic weight of a term is calculated with respect to its tag type, frequency of occurrence, and its relative position to an image. The weight of a term will be increased if other terms close-by have some semantic relationships with it, such as SYN (synonym), PART-OF, or IS-A. Color histogram, texture, and the shape are selected as the visual features and extracted in order to support visual-oriented retrieval.