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In this paper, we present a new multimedia retrieval paradigm to innovate large-scale search of heterogenous multimedia data. It is able to return results of different media types from heterogeneous data sources, e.g., using a query image to retrieve relevant text documents or images from different data sources. This utilizes the widely available data from(More)
Nowadays numerous social images have been emerging on the Web. How to precisely label these images is critical to image retrieval. However, traditional image-level tagging methods may become less effective because global image matching approaches can hardly cope with the diversity and arbitrariness of Web image content. This raises an urgent need for the(More)
This paper presents a novel Attribute-augmented Semantic Hierarchy (A<sup>2</sup> SH) and demonstrates its effectiveness in bridging both the semantic and intention gaps in Content-based Image Retrieval (CBIR). A<sup>2</sup> SH organizes the semantic concepts into multiple semantic levels and augments each concept with a set of related attributes, which(More)
Thrombin mediates the life-threatening cerebral edema and blood–brain barrier (BBB) damage that occurs after intracerebral hemorrhage (ICH). We previously found that the selective cannabinoid receptor 2 (CB2R) agonist JWH-133 reduced brain edema and neurological deficits following germinal matrix hemorrhage (GMH). We explored whether CB2R stimulation(More)
Wnt inhibitor factor-1 (WIF-1) is an extracellular antagonist of Wnts secreted proteins. Here we describe the expression pattern of Wif1 throughout the development of the mouse central nervous system (CNS). Wif1 mRNA can be detected as early as the developmental stage E11, and expression persists to adulthood. In embryonic stages, the level of Wif1(More)
In the above paper [1, p. 1679], the sentence " Yang et al. [?] integrated semisupervised learning and transfer learning techniques to exploit manually-labeled images for video tagging " Manuscript should have appeared as " Yang et al. [34] integrated semisuper-vised learning and transfer learning techniques to exploit manually labeled images for video(More)
Automatic media tagging plays a critical role in modern tag-based media retrieval systems. Existing tagging schemes mostly perform tag assignment based on community contributed media resources, where the tags are provided by users interactively. However, such social resources usually contain dirty and incomplete tags, which severely limit the performance of(More)
Data clustering is one of the fundamental research problems in data mining and machine learning. Most of the existing clustering methods, for example, normalized cut and (k)-means, have been suffering from the fact that their optimization processes normally lead to an NP-hard problem due to the discretization of the elements in the cluster indicator matrix.(More)