Topic models can be useful tools to discover latent topics in collections of documents.
Recent studies have shown the feasibility of approach topic modeling as a clustering task …

The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

Spatial stratified heterogeneity (SSH) refers to the geographical phenomena in which the
geographical attributes within-strata are more similar than the between-strata, which is …

Data growth in today's world is exponential, many applications generate huge amount of
data streams at very high speed such as smart grids, sensor networks, video surveillance …

Clustering incomplete instance is still a challenging task since missing values maybe make
the cluster information ambiguous, leading to the uncertainty and imprecision in results. This …

Approximate similarity queries on high-dimensional vector indices have become the
cornerstone for many critical online services. An increasing need for more sophisticated …

Argument summarisation is a promising but currently under-explored field. Recent work has
aimed to provide textual summaries in the form of concise and salient short texts, ie, key …

Abstract Study region Dongqing Reservoir located in Guizhou, China. Study focus Zoning
the RWTF (reservoir water temperature field) is of great significance and is an effective way …

The remaining discharge energy (RDE) of a battery is an important value for estimating the
remaining range of a vehicle. Prediction based methods for calculating RDE have been …

Since its early formulations, co-clustering has gained popularity and interest both within and
outside the machine learning community as a powerful learning paradigm for clustering high …