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International Journal of Data Mining Modelling and Management is a peer-reviewed journal published by Inderscience, covering Data Mining Algorithms and Applications, Data Management and Algorithms, Text and Document Classification Technologies.
| Publisher | Inderscience |
|---|---|
| Reference style | Author–year (Harvard/AGSM) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', International Journal of Data Mining Modelling and Management, 12(3), pp. 45–58.
Formats any DOI in International Journal of Data Mining Modelling and Management style. No sign-up. |
| Publishes research in | Data Mining Algorithms and Applications Data Management and Algorithms Text and Document Classification Technologies Complex Network Analysis Techniques Rough Sets and Fuzzy Logic |
| ISSN | 1759-1163 |
| Citation impact (2-yr) | 1.34 |
| h-index | 18 |
| i10-index | 44 |
| Total citations | 1,655 |
| Top institutions publishing here | Anna University, Chennai |
| Journal website | www.inderscience.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
In recent years, a number of machine learning algorithms have been developed for the problem of ordinal classification. These algorithms try to exploit, in one way or the other, the order information of the problem, essentially relying on the assumption that the ordinal structure of the set of class labels is also reflected in the…
Big data technology is popular and desirable among many users for handling, analysing, and storing large data.However, clustering the large data has become more complex due to its size.In recent years, several techniques have been presented to retrieve the information from big data.The proposed hybrid classifier model CSDHAP, the hybridised form of sun flower optimisation…
We explore how recent data mining-based tools developed in domains such as biomedicine or text mining for extracting interesting knowledge from sequence data could be applied to personal life course data. We focus on two types of approaches: 'survival' trees that attempt to partition the data into homogeneous groups regarding their survival characteristics, i.e., the…
Privacy-preserving record linkage is a very important task, mostly because of the very sensitive nature of the personal data. The main focus in this task is to find a way to match records from among different organisation data sets or databases without revealing competitive or personal information to non-owners. Towards accomplishing this task, several methods…
Accurate prediction is important in data mining and data classification. Rare events data, imbalanced or skewed datasets are very important in data mining and classification. However, These types of data are difficult to predict and to explain as has been demonstrated in the literature. The problems arise from various sources. This paper surveys the latest…
