A SOM-Based Information Organizer for Text and Video Data

摘要

We propose an information organizer for effective clustering and similarity-based retrieval of text and video data. Instead of giving keywords or authoring them, we use a vector space model and DCT image coding in order to extract characteristics of data. Data are clustered by Kohonen's self-organizing map, and the result is visualized in a 3D form. By this, similarity-based retrieval is achieved. We implemented a prototype system and report experimental results. We consider that our system effectively promotes reuse of distributed text and image data assets.