Ranking & Metrics
Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.
Research Impact Score:6.90
Contributing Best Scientists:225
H5-index:
Papers published by Best Scientists278
Research Ranking (Computer Science)50
Research Ranking (Computer Science)50
Conference Call for Papers
2022 5th International Conference on Data Mining and Big Data Analytics (DMBDA 2022) will be held in Shanghai, China during July 22-24, 2022 along with 2022 5th International Conference on Data Science and Information Technology (DSIT 2022). DMBDA 2022 is the workshop of DSIT 2022 which is co-organized by Shanghai Jiao Tong University, China and The International Society for Applied Computing (ISAC). DSIT 2022 is sponsored by IEEE, IEEE Shanghai Section, Shanghai Jiao Tong University, China, The International Society for Applied Computing (ISAC), and University of Santo Tomas, Philippines.
We fully understand some participants cannot attend the conference in-person due to COVID-19, so we will hold our conference both online and in-person, thus you could attend the conference online and do the online presentation.
DMBDA 2022 is intended as an international forum to bring together academicians, scientists, engineers, and researchers working in the fields of Data Mining and Big Data Analytics to exchange views, share their expertise, experience and research results, and discuss the challenges and future directions in their specialized areas.
During the upcoming conference, the invited renowned professors will share with us the recent innovations in the fields of Data Mining and Big Data Analytics. The conference will mainly feature on keynote speeches as well as peer-reviewed paper presentations. In addition, social program or academic visit will be arranged to encourage communication, discussion or cooperation among the researchers in this field.
We invite submissions of papers presenting an original high-quality research and development for the conference. All papers must be written in English and will be peer-reviewed by technical committees of the Conference and all accepted papers will be published in the conference proceedings.
Overview
Top Research Topics at International Conference on Data Mining?
Artificial intelligence (41.17%)
Data mining (36.04%)
Machine learning (25.22%)
The main research concerns discussed in International Conference on Data Mining are Artificial intelligence, Data mining, Machine learning, Cluster analysis and Pattern recognition.
The conference dives deep in exploring the relationship between the study of Artificial intelligence and Data modeling.
In it, Set (abstract data type) and Data set are investigated in conjunction with one another to address concerns in Data mining research.
It focuses on Machine learning research which is adjacent to topics in Training set.
The conference concentrates on Cluster analysis topics that focus on Correlation clustering, Fuzzy clustering, CURE data clustering algorithm, Clustering high-dimensional data and Canopy clustering algorithm.
Presentations on Correlation clustering include those discussing Data stream clustering, Constrained clustering, Single-linkage clustering and Consensus clustering.
What are the most cited papers published at the conference?
Collaborative Filtering for Implicit Feedback Datasets (2224 citations)
Research areas of the most cited articles at International Conference on Data Mining:
The most cited publications focus largely on the fields of Data mining, Artificial intelligence, Machine learning, Cluster analysis and Pattern recognition.
The conference publications facilitate discussions on Data mining that incorporate concepts from other fields like Scalability and Set (abstract data type).
Aside from discussions in Artificial intelligence, the most cited papers also deal with the subject of Text mining which intersects with Information retrieval disciplines.
What topics the last edition of the conference is best known for?
Artificial intelligence
Data mining
Machine learning
The previous edition focused in particular on these issues:
Artificial intelligence, Data mining, Machine learning, Cluster analysis and Pattern recognition are among the topics commonly tackled in International Conference on Data Mining.
Deep learning, Artificial neural network, Feature extraction, Classifier (UML) and Support vector machine studies are all carried out as a component of the study in Artificial intelligence presented.
The close relationship between Theoretical computer science and Graph (abstract data type) is one of the points of interest dissected in Data mining research.
The studies in Machine learning featured incorporate elements of Data modeling and Training set.
Research on Cluster analysis presented in International Conference on Data Mining focuses, in particular, on Correlation clustering, CURE data clustering algorithm, Fuzzy clustering, Canopy clustering algorithm and Clustering high-dimensional data.
The study on CURE data clustering algorithm featured in the conference expounds on the topic of Data stream clustering in particular.
The most cited articles from the last conference are:
CMAR: accurate and efficient classification based on multiple class-association rules (1118 citations)
Frequent subgraph discovery (990 citations)
Papers citation over time
A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
Research.com
Top authors and change over time
The top authors publishing at International Conference on Data Mining (based on the number of publications) are:
Philip S. Yu (46 papers) published 5 papers at the last edition, 4 more than at the previous edition,
Jiawei Han (27 papers) absent at the last edition,
Christos Faloutsos (26 papers) published 4 papers at the last edition, 1 less than at the previous edition,
Eamonn Keogh (23 papers) published 4 papers at the last edition the same number as at the previous edition,
Hui Xiong (23 papers) published 3 papers at the last edition, 2 less than at the previous edition.
The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.
Research.com
Top affiliations and change over time
Only papers with recognized affiliations are considered
The top affiliations publishing at International Conference on Data Mining (based on the number of publications) are:
IBM (131 papers) published 13 papers at the last edition, 2 less than at the previous edition,
Carnegie Mellon University (65 papers) published 11 papers at the last edition, 2 more than at the previous edition,
University of Illinois at Chicago (62 papers) published 6 papers at the last edition, 5 more than at the previous edition,
Microsoft (60 papers) published 2 papers at the last edition, 3 less than at the previous edition,
Tsinghua University (58 papers) published 3 papers at the last edition, 1 less than at the previous edition.
The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.
Research.com
Publication chance based on affiliation
The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
Research.com
During the most recent 2017 edition, 5.08% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 12.50% were posted by at least one author from the top 10 institutions publishing at the conference. Another 6.63% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 16.33% of all publications and 64.54% were from other institutions.
Returning Authors Index
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.
Research.com
Returning Institution Index
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Research.com
The experience to innovation index
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).
Research.com
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
