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
Ramesh Baral, Tao Li
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...... hiện toàn bộ
Exploring variable-length time series motifs in one hundred million length scale
Data Mining and Knowledge Discovery - Tập 32 - Trang 1200-1228 - 2018
Yifeng Gao, Jessica Lin
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...... hiện toàn bộ
Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series
Data Mining and Knowledge Discovery - - 2015
Bing Hu, Thanawin Rakthanmanon, Yuan Hao, S. Evans, Stefano Lonardi, Eamonn Keogh
Hypergraph Models and Algorithms for Data-Pattern-Based Clustering
Data Mining and Knowledge Discovery - Tập 9 - Trang 29-57 - 2004
Muhammet Mustafa Ozdal, Cevdet Aykanat
In traditional approaches for clustering market basket type data, relations among transactions are modeled according to the items occurring in these transactions. However, an individual item might induce different relations in different contexts. Since such contexts might be captured by interesting patterns in the overall data, we represent each transaction as a set of patterns through modifying t...... hiện toàn bộ
An adaptive algorithm for anomaly and novelty detection in evolving data streams
Data Mining and Knowledge Discovery - - 2018
Mohamed-Rafik Bouguelia, Sławomir Nowaczyk, Amir H. Payberah
Multiple Bayesian discriminant functions for high-dimensional massive data classification
Data Mining and Knowledge Discovery - Tập 31 - Trang 465-501 - 2016
Jianfei Zhang, Shengrui Wang, Lifei Chen, Patrick Gallinari
The presence of complex distributions of samples concealed in high-dimensional, massive sample-size data challenges all of the current classification methods for data mining. Samples within a class usually do not uniformly fill a certain (sub)space but are individually concentrated in certain regions of diverse feature subspaces, revealing the class dispersion. Current classifiers applied to such ...... hiện toàn bộ
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
Min Wang, Yee Leung, Chenhu Zhou, Tao Pei, Jiancheng Luo
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...... hiện toàn bộ
A fast and effective method to find correlations among attributes in databases
Data Mining and Knowledge Discovery - Tập 14 - Trang 367-407 - 2007
Elaine P. M. de Sousa, Caetano Traina, Agma J. M. Traina, Leejay Wu, Christos Faloutsos
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...... hiện toàn bộ
ABACUS: frequent pAttern mining-BAsed Community discovery in mUltidimensional networkS
Data Mining and Knowledge Discovery - Tập 27 - Trang 294-320 - 2013
Michele Berlingerio, Fabio Pinelli, Francesco Calabrese
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...... hiện toàn bộ
Binary matrix factorization for analyzing gene expression data
Data Mining and Knowledge Discovery - Tập 20 - Trang 28-52 - 2009
Zhong-Yuan Zhang, Tao Li, Chris Ding, Xian-Wen Ren, Xiang-Sun Zhang
The advent of microarray technology enables us to monitor an entire genome in a single chip using a systematic approach. Clustering, as a widely used data mining approach, has been used to discover phenotypes from the raw expression data. However traditional clustering algorithms have limitations since they can not identify the substructures of samples and features hidden behind the data. Differen...... hiện toàn bộ
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