Similarity search in multimedia databases requires an efficient support of nearest neighbor search on a large set of high-dimensional points. A technique applied for similarity search in multimedia databases is to transform important properties of the multimedia objects into points of a high-dimensional feature space. The feature space is usually indexed using a multidimensional index structure...

The measurement of semantic similarity between words is very important in many applicaitons. In this paper, we propose a method based on Laplacian eigenmaps to measure semantic similarity between words. First, we attach semantic features to each word. Second, a similarity matrix ,which semantic features are encoded into, is calculated in the original high-dimensional space. Finally, with the ai...

In general, young children focus on holistic similarity and older children focus on dimensional similarity (selectively attending to one property, such as brightness, to the exclusion of others, such as size). Research on early word learning, however, suggests the process of learning words trains attention to category-relevant dimensions. We ask: does word learning scaffold dimensional attentio...

Human gait decision was carried out with the help of similarity measure design. Gait signal was selected through hardware implementation including all in one sensor, control unit, and notebook with connector. Each gait signal was considered as high dimensional data. Therefore, high dimensional data analysis was considered via heuristic technique such as the similarity measure. Each human patter...

Video signatures are compact representations of video sequences designed for efficient similarity measurement. In this paper, we propose a feature extraction technique to support fast similarity search on large databases of video signatures. Our proposed technique transforms the high dimensional video signatures into low dimensional vectors where similarity search can be efficiently performed. ...

Similarity joins represent a useful operator for data mining, data analysis and data exploration applications. With the exponential growth of data to be analyzed, distributed approaches like MapReduce are required. So far, the state-of-the-art similarity join approaches based on MapReduce mainly focused on the processing of low-dimensional vector data. In this paper, we revisit and investigate ...