Learning compact hashing codes for efficient tag completion and prediction

Abstract

Tags have been popularly utilized in many applications with image and text data for better managing, organizing and searching for useful information. Tag completion provides missing tag information for a set of existing images or text documents while tag prediction recommends tag information for any new image or text document. Valuable prior research has focused on improving the accuracy of tag completion and prediction, but limited research has been conducted for the efficiency issue in tag completion and prediction, which is a critical problem in many large scale real world applications.