document: OCTOPUS : aggressive search of multi-modality data using multifaceted knowledge base An important trend in Web information processing is the support of multimedia retrieval . However , the most prevailing paradigm for multimedia retrieval , content-based retrieval ( CBR ) , is a rather conservative one whose performance depends on a set of specifically defined low-level features and a carefully chosen sample object . In this paper , an aggressive search mechanism called Octopus is proposed which addresses the retrieval of multi-modality data using multifaceted knowledge . In particular , Octopus promotes a novel scenario in which the user supplies seed objects of arbitrary modality as the hint of his information need , and receives a set of multi-modality objects satisfying his need . The foundation of Octopus is a multifaceted knowledge base constructed on a layered graph model ( LGM ) , which describes the relevance between media objects from various perspectives . Link analysis based retrieval algorithm is proposed based on the LGM . A unique relevance feedback technique is developed to update the knowledge base by learning from user behaviors , and to enhance the retrieval performance in a progressive manner . A prototype implementing the proposed approach has been developed to demonstrate its feasibility and capability through illustrative examples .
doc_bio_tags: O O O O O O O O B I I O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O B I I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O