Data Mining and Knowledge Discovery
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Exploiting the roles of aspects in personalized POI recommender systems
Data Mining and Knowledge Discovery - Tập 32 - Trang 320-343 - 2017
The evolution of World Wide Web (WWW) and the smart-phone technologies have revolutionized our daily life. This has facilitated the emergence of many useful systems, such as Location-based Social Networks (LBSN) which have provisioned many factors that are crucial for selection of Point-of-Interests (POI). Some of the major factors are: (i) the location attributes, such as geo-coordinates, categor......
Exploring variable-length time series motifs in one hundred million length scale
Data Mining and Knowledge Discovery - Tập 32 - Trang 1200-1228 - 2018
The exploration of repeated patterns with different lengths, also called variable-length motifs, has received a great amount of attention in recent years. However, existing algorithms to detect variable-length motifs in large-scale time series are very time-consuming. In this paper, we introduce a time- and space-efficient approximate variable-length motif discovery algorithm, Distance-Propagation......
Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series
Data Mining and Knowledge Discovery - - 2015
An adaptive algorithm for anomaly and novelty detection in evolving data streams
Data Mining and Knowledge Discovery - - 2018
A Mathematical Morphology Based Scale Space Method for the Mining of Linear Features in Geographic Data
Data Mining and Knowledge Discovery - Tập 12 - Trang 97-118 - 2006
This paper presents a spatial data mining method MCAMMO and its extension L_MCAMMO designed for discovering linear and near linear features in spatial databases. L_MCAMMO can be divided into two basic steps: first, the most suitable re-segmenting scale is found by MCAMMO, which is a scale space method with mathematical morphology operators; second, the segmented result at this scale is re-segmente......
A fast and effective method to find correlations among attributes in databases
Data Mining and Knowledge Discovery - Tập 14 - Trang 367-407 - 2007
The problem of identifying meaningful patterns in a database lies at the very heart of data mining. A core objective of data mining processes is the recognition of inter-attribute correlations. Not only are correlations necessary for predictions and classifications – since rules would fail in the absence of pattern – but also the identification of groups of mutually correlated attributes expedites......
ABACUS: frequent pAttern mining-BAsed Community discovery in mUltidimensional networkS
Data Mining and Knowledge Discovery - Tập 27 - Trang 294-320 - 2013
Community discovery in complex networks is the problem of detecting, for each node of the network, its membership to one of more groups of nodes, the communities, that are densely connected, or highly interactive, or, more in general, similar, according to a similarity function. So far, the problem has been widely studied in monodimensional networks, i.e. networks where only one connection between......
K-plex cover pooling for graph neural networksAbstract Graph pooling methods provide mechanisms for structure reduction that are intended to ease the diffusion of context between nodes further in the graph, and that typically leverage community discovery mechanisms or node and edge pruning heuristics. In this paper, we introduce a novel pooling technique which borrows from classical results in graph theory that... ...
Data Mining and Knowledge Discovery - - 2021
Guest editorial: special issue on temporal data mining: theory, algorithms and applications
Data Mining and Knowledge Discovery - Tập 16 - Trang 1-3 - 2007
This special issue provides a leading forum for timely, in-depth presentation of recent advances in algorithms, theories and applications in temporal data mining. The selected papers underwent a rigorous refereeing and revision process.
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