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Springer

The 19th Pacific Rim International Conference on Artificial Intelligence (PRICAI)

Location: Shanghai , China

Submission deadline: 6/15/2022

Conference dates: 11/10/2022 - 11/13/2022

Research H-index
5

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 669 22 25 5

Call for Papers

The conference areas of interest include, but are not limited to:

AI foundations
Applications of AI
Agents
Bayesian networks
Big data analytics
Bioinformatics
Bio-inspired intelligence
Cognitive systems
Cognitive computing
Constraint satisfaction
Data mining and knowledge discovery
Decision theory
Education and tutoring systems
Evolutionary computation
Games and interactive entertainment
Heuristics
Information retrieval and extraction
Internet of things
Knowledge acquisition and ontology
Knowledge management
Knowledge representation
Law, Ethics and AI
Linked open data
Machine learning
Markov networks
Multimedia and arts
Multimodal interaction
Natural language processing
Neural networks and deep learning
Planning and scheduling
Probabilistic inference
Reasoning
Robotics
Search
Text/Web/Internet mining
Semantic Web
Social intelligence
Speech and dialogue systems
Uncertainty
Vision and perception

Overview

This ranking presents a comprehensive list of scientific conferences from the field of Computer Science, meticulously curated to provide researchers and professionals with authoritative insights into the most impactful venues for scholarly dissemination. The ranking has been prepared by Research.com, recognized as one of the leading websites for science research across all major fields, including Computer Science, and has been providing trusted data on scientific contributions since 2014.

The position that each conference occupies within this ranking is determined by a unique bibliometric score developed by Research.com. This score is calculated based on the estimated h-index and the number of leading scientists who have participated in the conference over the last three years. The assessment relies on comprehensive data, including Impact Score values gathered as of 2024-11-27, ensuring that the ranking reflects the most current trends in scholarly influence.

The ranking process involved an in-depth examination of more than 2,742 conferences, selected through a rigorous inspection of over 148,739 scientific documents published in the last three years. These documents represent the contributions of 13,184 leading and well-respected scientists in the area of Computer Science. This extensive approach underscores the depth of research and sophisticated analysis executed by experts, reinforcing the credibility and relevance of the resulting conference ranking.

For a detailed explanation of the methodology employed in computing the ranking scores, including information on bibliometric metrics and the expert-driven evaluation process, please visit 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 Rim International Conference on Artificial Intelligence (based on the number of publications) are:

  • Minjie Zhang (11 papers) published 2 papers at the last edition, 1 less than at the previous edition,
  • Fenghui Ren (9 papers) published 2 papers at the last edition, 1 less than at the previous edition,
  • Kazumi Saito (9 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • Abdul Sattar (9 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • Quan Bai (8 papers) published 1 paper at the last edition, 3 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 Rim International Conference on Artificial Intelligence (based on the number of publications) are:

  • Nanjing University (27 papers) published 13 papers at the last edition, 8 more than at the previous edition,
  • Chinese Academy of Sciences (20 papers) published 6 papers at the last edition, 3 more than at the previous edition,
  • Griffith University (18 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • Tianjin University (14 papers) published 9 papers at the last edition, 6 more than at the previous edition,
  • Osaka University (13 papers) published 1 paper at the last edition the same number as 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 2018 edition, 4.26% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 29.63% were posted by at least one author from the top 10 institutions publishing at the conference. Another 12.59% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 25.19% of all publications and 32.59% 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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