ISSN: 1384-5810

Journal Guideline

Data Mining and Knowledge Discovery Q1 Unclaimed

Springer Netherlands Netherlands

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The premier technical publication in the field, Data Mining and Knowledge Discovery is a resource collecting relevant common methods and techniques and a forum for unifying the diverse constituent research communities. The journal publishes original technical papers in both the research and practice of data mining and knowledge discovery, surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications. Coverage includes: - Theory and Foundational Issues - Data Mining Methods - Algorithms for Data Mining - Knowledge Discovery Process - Application Issues. The premier technical journal focused on the theory, techniques and practice for extracting information from large databases. Publishes original technical papers in both the research and practice of data mining and knowledge discovery, surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications. It has an SJR impact factor of 1,813.

Type: Journal

Type of Copyright:

Languages: English

Open Access Policy: Open Choice

Type of publications:

Publication frecuency: -

Categories: Computer Networks and Communications (Q1) Computer Science Applications (Q1) Information Systems (Q1)

Price

2290 €

Inmediate OA

NPD

Embargoed OA

0 €

Non OA

Metrics

1,813

SJR Impact factor

117

H Index

93

Total Docs (Last Year)

218

Total Docs (3 years)

5350

Total Refs

1455

Total Cites (3 years)

215

Citable Docs (3 years)

4.56

Cites/Doc (2 years)

57.53

Ref/Doc

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Aims and Scope

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A systematic approach to the assessment of fuzzy association rules

Ratio Selection for Classification Models

Editorial

Weakly supervised nonnegative matrix factorization for user-driven clustering

Fast incremental mining of web sequential patterns with PLWAP tree

Decomposition-by-normalization (DBN): leveraging approximate functional dependencies for efficient CP and tucker decompositions

Collusion set detection using graph clustering

Dynamic graph summarization: a tensor decomposition approach

Summarizing transactional databases with overlapped hyperrectangles

Sourcerer: mining and searching internet-scale software repositories

DECODE: a new method for discovering clusters of different densities in spatial data

Sequential Activity Profiling: Latent Dirichlet Allocation of Markov Chains

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Support measures for graph data*

Mining periodic behaviors of object movements for animal and biological sustainability studies

Tree Structures for Mining Association Rules

Dynamic inference of social roles in information cascades

MassExodus: modeling evolving networks in harsh environments

Mining process models with non-free-choice constructs

Cluster validity functions for categorical data: a solution-space perspective

GA-TVRC-Het: genetic algorithm enhanced time varying relational classifier for evolving heterogeneous networks

Spatial autocorrelation and entropy for renewable energy forecasting

Mining significant association rules from uncertain data

Mining strong relevance between heterogeneous entities from unstructured biomedical data

Publishing anonymous survey rating data