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International Journal of Data Science and Analytics


International Journal of Data Science and Analytics OnlineFirst articles

02.08.2022 | Regular Paper

Attention-like feature explanation for tabular data

A new method for local and global explanation of the machine learning black-box model predictions by tabular data is proposed. It is implemented as a system called AFEX (Attention-like Feature EXplanation) and consisting of two main parts. The …

Open Access 30.07.2022 | Regular Paper

Optimizing graph layout by t-SNE perplexity estimation

Perplexity is one of the key parameters of dimensionality reduction algorithm of t-distributed stochastic neighbor embedding (t-SNE). In this paper, we investigated the relationship of t-SNE perplexity and graph layout evaluation metrics including …

Open Access 25.07.2022 | Regular Paper

Data-driven versus a domain-led approach to k-means clustering on an open heart failure dataset

Domain-driven data mining of health care data poses unique challenges. The aim of this paper is to explore the advantages and the challenges of a ‘domain-led approach’ versus a data-driven approach to a k-means clustering experiment. For the …

24.07.2022 | Regular Paper

Semantic enhanced Markov model for sequential E-commerce product recommendation

To model sequential relationships between items, Markov Models build a transition probability matrix $$\mathbf {P}$$ P of size $$n \times n$$ n × n , where n represents number of states (items) and each matrix entry $$p_{(i,j)}$$ p ( i , j ) …

20.07.2022 | Regular Paper

PARAS: a parameter space-driven approach for complete association rule mining

To enable efficient association rule mining, existing techniques prestore intermediate results as itemsets. However, the actual rule generation is still performed at query-time. The response time thus tends to remain unacceptably long for …

Über diese Zeitschrift

Data-driven scientific discovery is a key emerging paradigm driving research innovation and industrial development in domains such as business, social sci­ence, the Internet of Things, and cloud computing. The field encompasses the larger ar­eas of data analytics, machine learning, and managing big data, while related new sci­entific chal­lenges range from data capture, creation, storage, search, sharing, analysis, and vis­ualization, to integration across heterogeneous, interdependent complex resources for real-time decision-making, collaboration, and value creation. The journal welcomes experimental and theoretical findings on data science and advanced analytics along with their applications to real-life situations.

International Journal of Data Science and Analytics
Jahrgang 1/2016 - Jahrgang 14/2022
Springer International Publishing
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