Rapid progress and superior performance have been achieved for skeleton-based action recognition recently. In this article, we investigate problem under a cross-dataset setting, which is new, pragmatic, challenging task in real-world scenarios. Following the unsupervised domain adaptation (UDA) paradigm, labels are only available on source dataset, but unavailable target dataset training stage....

Detecting outliers which are grossly different from or inconsistent with the remaining spatio-temporal dataset is a major challenge in real-world knowledge discovery and data mining applications. In this paper, we deal with the outlier detection problem in spatio-temporal data and we describe a rough set approach that finds the top outliers in an unlabeled spatio-temporal dataset. The proposed ...

Time in geographic information systems has been a research theme for more than two decades, resulting in comprehensive theoretical work, many research prototypes and several working solutions. However, none of the available solutions provides the ability to manage, analyze, process and visualize large environmental spatio-temporal datasets and the investigation and assessment of temporal relati...

We created a dataset of syntactic-ngrams (counted dependency-tree fragments) based on a corpus of 3.5 million English books. The dataset includes over 10 billion distinct items covering a wide range of syntactic configurations. It also includes temporal information, facilitating new kinds of research into lexical semantics over time. This paper describes the dataset, the syntactic representatio...

We present a novel action representation based on encoding the global temporal movement of an action. We represent an action as a set of movement pattern histograms that encode the global temporal dynamics of an action. Our key observation is that temporal dynamics of an action are robust to variations in appearance and viewpoint changes, making it useful for action recognition and retrieval. W...

Mining patterns from fuzzy temporal data is an important data mining problem. One of these mining task is to find locally frequent sets, In most of the earlier works fuzziness was considered in the time attribute of the datasets .Although a couple of works have been done in dealing with such data, little has been done on the implementation side. In this article, we propose an efficient implemen...