As increasingly more textual information becomes available, named entity recognition (NER) systems are thriving, benefiting from powerful models and expressive tagging schemes that promote the full use of diverse features at different levels. To improv…
Community detection is of great help to understand the structures and functions of complex networks. It has become one of popular research topics in the field of complex networks analysis. Due to the simplicity, flexibility, effectiveness and better in…
Multi-view outlier detection has a wide range of applications and has been well investigated in recent years. However, 1) most existing state-of-the-art methods cannot efficiently handle outlier detection problem for large-scale multi-view data, since …
We present an unsupervised multi-view partial least squares (PLS) by learning a common latent space from given multi-view data. Although PLS is a frequently used technique for analyzing relationships between two datasets, its extension to more than two…
This article presents a new holistic and efficient approach to big data analysis. We introduce a new parallel algorithm, known as ATrie Group Join (ATGJ), that integrates join, grouping and aggregation operations to accelerate big data analytical workl…
Intuitively, word representation for logographic languages like Chinese can be enhanced by its internal characteristics. Several research endeavors tried to learn Chinese word embeddings with characters, radicals, or subcharacters containing rich seman…
Predicting air pollution concentration is crucial and beneficial for public health. This study proposes a domain-specific Bayesian deep-learning model for long-term air pollution forecast in China and the United Kingdom. Our proposed model carries thre…
Symmetric high-dimensional and sparse (SHiDS) networks are frequently found in various industrial applications. A symmetric non-negative latent factor (SNLF) model can acquire essential features from them precisely, yet it suffers from slow convergence…
The booming of multimedia technologies has promoted the diversity of visual big data. To learn common features across heterogeneous image data, the image co-processing has exhibited its advantages over the separate one. Recently, an active topic of ima…
Directed and undirected probabilistic graphical models have been successfully used in community detection in recent years, but existing graphical model based methods usually only use one type of probabilistic graphical model to discover communities. Ho…