The Indian Journal of Data Mining (IJDM) is half yearly international journal, being published in the months of May and November by Lattice Science Publication (LSP) Bhopal (M.P.), India since year 2021. The aim of the journal is to:
- disseminate original, scientific, theoretical or applied research in the field of Data Mining.
- dispense a platform for publishing results and research with a strong empirical component.
- aqueduct the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
- seek original and unpublished research article(s) based on theoretical and experimental works for the publication globally.
- publish original, theoretical and practical advances in Data Mining.
- impart a platform for publishing results and research with a strong empirical component, to create a bridge for significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
- solicit original and unpublished research article(s), based on theoretical and experimental works.
The Indian Journal of Data Mining (IJDM) is not limited to a specific aspect of Data Mining but is instead devoted to a wide range of subfields in the Data Mining. While it encourages a broad spectrum of contribution in the Data Mining, its core interest lies in issues concerning Data Mining. Articles of interdisciplinary nature are particularly welcome.
The primary goal of the new editors is to maintain high quality of publications. There will be a commitment to expediting the time taken for the publication of the article(s). The articles that are sent for reviews will have names of the authors deleted with a view towards enhancing the objectivity and fairness of the review process.
Articles that are devoted to the purely mathematical aspects without a discussion of the physical implications of the results or the consideration of specific examples are discouraged. Articles concerning Data Mining should not be limited merely to a description and recording of observations but should contain theoretical and quantitative discussion of the results.
The Editors reserve the right to reject article(s) without sending them out for review. Articles for the Regular Issue of the journal can submit, round the year, electronically by using Article Submission System. The summited article (s) should cover following subfields of Data Mining:
- Data Mining
- Data Science
- Big Data
- Data Warehouse
- Big DaaS
- Scalable Computing
- Cloud Computing
- Knowledge Discovery
- Information Retrieval
- Social Data and Semantics
- Mining Functions
- Data Regression
- Data Classification
- Anomaly Detection
- Data Clustering
- Data Association
- Data Regression
- Data Cleaning
- Feature Selection and Extraction
- Data Mining Algorithms
- Decision Tree
- Generalized Linear Models
- Minimum Description Length
- Naive Bayes
- Non-Negative Matrix Factorization
- Support Vector Machines
- Data Preparation
- Mining Unstructured Data
- Artificial Intelligence
- Future Directions and Challenges in Data Mining
- Industrial Challenges in Data Mining