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Springer

PAKDD 2027 — 31st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)

Location: Victoria University of Wellington, Wellington , New Zealand

Conference dates: 6/29/2027 - 7/2/2027

Research H-index
11

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 170 112 117 16

Call for Papers

PAKDD is the leading Pacific-Asia conference on knowledge discovery and data mining, with proceedings in Springer LNAI. It invites original contributions on data mining, machine learning, knowledge discovery, deep learning, graph mining, recommender systems, big data analytics. Submissions may take the form of full research papers, extended abstracts and poster presentations reporting theoretical, computational and experimental work, as well as industrial case studies and applications. The meeting brings together researchers, engineers, industry practitioners and students to exchange recent results and discuss emerging directions in the field. Accepted papers are published in a Springer proceedings volume.

Overview

This comprehensive ranking presents a curated list of scientific conferences within the field of Computer Science, meticulously evaluated and assembled by Research.com. Recognized since 2014 as one of the leading platforms for science research across all major disciplines, Research.com is dedicated to delivering trusted and authoritative data on scientific contributions.

The position of each conference in this ranking is determined according to a unique bibliometric score developed by Research.com. This score integrates both the estimated h-index and the number of leading scientists who have participated or presented at the conference within the last three years, offering a multifaceted assessment of conference influence and prominence.

To ensure the reliability and depth of this ranking, the evaluation process encompassed an extensive review of over 2,742 conferences. These were selected following a rigorous inspection and critical analysis of more than 148,739 scientific documents authored by 13,184 distinguished and reputable Computer Science experts over the last three years. The collection and analysis of Impact Score values were completed as of 2024-11-27.

For those seeking a deeper understanding of the methodologies and bibliometric techniques applied in forming these rankings, detailed information is available on our Methodology Page.

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.

The top authors publishing at Pacific-Asia Conference on Knowledge Discovery and Data Mining (based on the number of publications) are:

  • Svetha Venkatesh (16 papers) absent at the last edition,
  • Christos Faloutsos (15 papers) published 1 paper at the last edition the same number as at the previous edition,
  • Dinh Phung (15 papers) absent at the last edition,
  • Peter Christen (14 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • Philip S. Yu (11 papers) published 1 paper at the last edition, 1 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.

Only papers with recognized affiliations are considered

The top affiliations publishing at Pacific-Asia Conference on Knowledge Discovery and Data Mining (based on the number of publications) are:

  • Chinese Academy of Sciences (40 papers) published 17 papers at the last edition, 15 more than at the previous edition,
  • Tsinghua University (30 papers) published 8 papers at the last edition, 5 more than at the previous edition,
  • Nanjing University (27 papers) published 10 papers at the last edition, 7 more than at the previous edition,
  • University of Technology, Sydney (27 papers) published 7 papers at the last edition, 4 more than at the previous edition,
  • Deakin University (21 papers) published 1 paper at the last edition, 2 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.

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.

During the most recent 2019 edition, 1.20% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 32.73% were posted by at least one author from the top 10 institutions publishing at the conference. Another 7.27% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.82% of all publications and 38.18% 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.

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.

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).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

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