Mapreduce Function in Hadoop forMining Weakly Labeled Web Facial Images for Search Based Face Annotation

Web mining is the application of data mining techniques to discover patterns from the Web. The main objective of web mining is to develop more intelligent tools for potentially help the user in finding, extracting, filtering and evaluating valuable information and resources. The popularity of digital images is rapidly increasing due to improving digital imaging technologies and convenient availability facilitated by the Internet. To improve the retrieval accuracy of content-based image retrieval systems, the research focus has been shifted from designing sophisticated low-level feature extraction algorithms to reducing the ‘semantic gap’ between the visual features and the richness of human semantics. Search-Based Face Annotation (SBFA) by mining weakly labelled facial images that are freely available on the World Wide Web (WWW). One challenging problem for search-based face annotation scheme is to effectively perform annotation by exploiting the list of most similar facial images and weak labels that are often noisy and incomplete. To overcome the above issues, a map reducing technique is developed to improve the efficiency and scalability of the images. Map reduce program is composed of a map procedure that performs filtering and sorting.