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ACL

TextGraphs-16: Graph-based Methods for Natural Language Processing (TextGraphs)

Location: Gyeongju , Korea

Submission deadline: 7/11/2022

Conference dates: 10/12/2022 - 10/17/2022

Research H-index
7

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 542 15 16 7

Call for Papers

TextGraphs-16 invites submissions on (but not limited to) the following topics

Graph-based and graph-supported machine learning methods: Graph embeddings and their combinations with text embeddings; Graph-based and graph-supported deep learning (e.g., graph-based recurrent and recursive networks); Probabilistic graphical models and structure learning methods

Graph-based methods for Information Retrieval and Extraction: Graph-based methods for word sense disambiguation; Graph-based strategies for semantic relation identification; Encoding semantic distances in graphs; Graph-based techniques for text summarization, simplification, and paraphrasing; Graph-based techniques for document navigation and visualization

New graph-based methods for NLP applications: Random walk methods in graphs; Semi-supervised graph-based methods

Graph-based methods for applications on social networks

Graph-based methods for NLP and Semantic Web: Representation learning methods for knowledge graphs; Using graphs-based methods to populate ontologies using textual data

Overview

This comprehensive ranking showcases a meticulously curated list of scientific conferences from the field of Computer Science. Developed by Research.com — a preeminent authority in providing trusted data on scientific contributions across all major disciplines since 2014 — this ranking serves as a definitive resource for researchers, academics, and professionals seeking to identify the most impactful venues in Computer Science research.

Each conference’s position within the ranking is determined by an exclusive bibliometric score devised by Research.com experts. This score is computed based on a combination of the estimated h-index and the number of leading scientists who have participated in the conference over the three most recent years. This dual-faceted approach provides a robust measure of both the long-term scholarly impact and the current prestige of each event.

The 2024 edition of the ranking contains Impact Score values collected on 2024-11-27. In order to ensure the highest level of academic rigor and accuracy, the process involved a thorough evaluation of more than 2,742 conferences. These conferences were selected following an exhaustive review of over 148,739 scientific documents published in the past three years by 13,184 of the most prominent and respected scientists within the Computer Science community.

The legitimacy and credibility of this ranking are underpinned by the extensive research, complex analysis, and domain expertise of the Research.com team. For those interested in an in-depth understanding of the methodologies and calculations underpinning these scores, comprehensive details are 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 Graph-based Methods for Natural Language Processing (based on the number of publications) are:

  • Daniel Ramage (2 papers) absent at the last edition,
  • Ahmed E. Hassan (2 papers) published 2 papers at the last edition,
  • Christopher D. Manning (2 papers) absent at the last edition,
  • Swapna Somasundaran (2 papers) absent at the last edition,
  • Dragomir R. Radev (2 papers) published 1 paper at the last edition the same number as 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 Graph-based Methods for Natural Language Processing (based on the number of publications) are:

  • University of Michigan (2 papers) published 1 paper at the last edition the same number as at the previous edition,
  • Stanford University (2 papers) absent at the last edition,
  • Microsoft (2 papers) published 2 papers at the last edition,
  • Johns Hopkins University (2 papers) absent at the last edition,
  • University of Haifa (1 papers) published 1 paper at the last 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 2012 edition, 11.11% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 37.50% were posted by at least one author from the top 10 institutions publishing at the conference. Another 37.50% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 25.00% of all publications and 0.00% 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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