Graph learning based recommender systems: A review
Recent years have witnessed the fast development of the emerging topic of Graph Learning
based Recommender Systems (GLRS). GLRS employ advanced graph learning …
based Recommender Systems (GLRS). GLRS employ advanced graph learning …
Astronomical image and data analysis
With information and scale as central themes, this comprehensive survey explains how to
handle real problems in astronomical data analysis using a modern arsenal of powerful …
handle real problems in astronomical data analysis using a modern arsenal of powerful …
[KSIĄŻKA][B] Data classification
CC Aggarwal, CC Aggarwal - 2015 - Springer
The classification problem is closely related to the clustering problem discussed in Chaps. 6
and 7. While the clustering problem is that of determining similar groups of data points, the …
and 7. While the clustering problem is that of determining similar groups of data points, the …
[KSIĄŻKA][B] Encyclopedia of machine learning
This comprehensive encyclopedia, with over 250 entries in an AZ format, provides easy
access to relevant information for those seeking entry into any aspect within the broad field …
access to relevant information for those seeking entry into any aspect within the broad field …
[KSIĄŻKA][B] An introduction to information retrieval
CD Manning - 2009 - edl.emi.gov.et
As recently as the 1990s, studies showed that most people preferred getting information
from other people rather than from information retrieval systems. Of course, in that time …
from other people rather than from information retrieval systems. Of course, in that time …
Orthogonal nonnegative matrix t-factorizations for clustering
Currently, most research on nonnegative matrix factorization (NMF) focus on 2-factor
X=FG^T factorization. We provide a systematicanalysis of 3-factor X=FSG^T NMF. While it …
X=FG^T factorization. We provide a systematicanalysis of 3-factor X=FSG^T NMF. While it …
On the equivalence of nonnegative matrix factorization and spectral clustering
Current nonnegative matrix factorization (NMF) deals with X= FGT type. We provide a
systematic analysis and extensions of NMF to the symmetric W= HHT, and the weighted W …
systematic analysis and extensions of NMF to the symmetric W= HHT, and the weighted W …
Large scale spectral clustering via landmark-based sparse representation
Spectral clustering is one of the most popular clustering approaches. However, it is not a
trivial task to apply spectral clustering to large-scale problems due to its computational …
trivial task to apply spectral clustering to large-scale problems due to its computational …
A min-max cut algorithm for graph partitioning and data clustering
An important application of graph partitioning is data clustering using a graph model-the
pairwise similarities between all data objects form a weighted graph adjacency matrix that …
pairwise similarities between all data objects form a weighted graph adjacency matrix that …
Hierarchical clustering algorithms for document datasets
Fast and high-quality document clustering algorithms play an important role in providing
intuitive navigation and browsing mechanisms by organizing large amounts of information …
intuitive navigation and browsing mechanisms by organizing large amounts of information …