Submission Deadline: Wednesday 20 Apr 2022
Conference Dates: Jul 22, 2022 - Jul 24, 2022
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.
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.
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.
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.
The top authors publishing at International Conference on Data Mining (based on the number of publications) are:
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.
Only papers with recognized affiliations are considered
The top affiliations publishing at International Conference on Data Mining (based on the number of publications) are:
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.
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.
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.
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.
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.
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:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Jul 23, 2021 - Jul 25, 2021
Jul 22, 2022 - Jul 24, 2022
5th International Conference on Data Mining and Big Data Analytics
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