Identifying patterns and associations in data is fundamental to discovery in science. This work investigates a very simple instance of the problem, where each data point consists of a vector of binary attributes, and attributes are treated equally. For example, each data point may correspond to a person and the attributes may be their sex, whether they smoke cigarettes, whether they have been d...

Time series clustering algorithms have been widely used to mine the clustering distribution characteristics of real phenomena. However, these algorithms have several limitations. First, they depend heavily on prior knowledge. Second, the algorithms do not simultaneously consider the similarity of spatial locations, spatial-temporal attribute values, and spatial-temporal attribute trends (trends...

Localized multiple kernel learning (LMKL) is an attractive strategy for combining multiple heterogeneous features in terms of their discriminative power for each individual sample. However, models excessively fitting to a specific sample would obstacle the extension to unseen data, while a more general form is often insufficient for diverse locality characterization. Hence, both learning sample...

One of the most important factors in quality improvement of transportation, communication, accommodation, utilities, etc is urban infrastructures development. Certainly, with the intention of achieving the goal, approaches to urban infrastructures management must be ranked by Scientific and logical evaluation and calculation. This paper presents evaluation of governmental, private, and public–p...

In this paper we construct three primitive mappings based on three kinds of genetic attribute equivalences. We then apply the mappings and basic addition operation to the universal genetic code to generate three square matrices. We show that these square matrices are stochastic in nature. They demonstrate some fractal similarity properties and resemble the similar properties to the original sto...

Measuring visual similarity is critical for image understanding. But what makes two images similar? Most existing work on visual similarity assumes that images are similar because they contain the same object instance or category. However, the reason why images are similar is much more complex. For example, from the perspective of category, a black dog image is similar to a white dog image. How...

Image retrieval and ranking based on the multi-attribute queries is beneficial to various real world applications. Traditional methods on this problem often utilize intermediate representations generated by attribute classifiers to describe the images, and then the images in the database are sorted according to their similarities to the query. However, such a scheme has two main challenges: 1) ...