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Proceedings of the VLDB Endowment
H-index 56

Proceedings of the VLDB Endowment

2150-8097

Published by: ACM

https://dl.acm.org/journal/pvldb

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 57 424 1072 56

Additional Metrics

Number of Best Scientists*: 480
Documents by Best Scientists*: 1096
Top 100 Ranked Scientists*: 15
SCIMAGO H-index: 165
SCIMAGO SJR: 1.832
Impact Factor: 3.3

Overview

Top Research Topics at Proceedings of The Vldb Endowment?

The journal is mainly concerned with subjects like Human–computer interaction, Work (electrical), Information retrieval, Data exploration and Data search. While Information retrieval is the focus of the conference, it also discussed overlapping research pursuits in other fields like Wireless sensor network, Stream data and Location-based service.

  • Human–computer interaction (33.33%)
  • Work (electrical) (33.33%)
  • Information retrieval (33.33%)

Papers citation over time

Insufficient data to conduct the analysis

The top authors publishing in Proceedings of The Vldb Endowment (based on the number of publications) are:

  • Elisa Bertino (2 papers) absent at the last edition,
  • Elke A. Rundensteiner (2 papers) absent at the last edition,
  • Rimma V. Nehme (2 papers) absent at the last edition,
  • Karen Works (1 papers) absent at the last edition,
  • Pierre Bourhis (1 papers) published 1 paper at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

Insufficient data to conduct the analysis

Publication chance based on affiliation

Insufficient data to conduct the analysis

Returning Authors Index

Insufficient data to conduct the analysis

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, 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).

Career Opportunities Within the Field

While studying and conducting research within this field, several career options may open up for interested individuals. These professions not only offer opportunities to implement and further investigate the concepts discussed in the Proceedings of The VLDB Endowment but lend a practical aspect to the theoretical knowledge garnered.

An example is a high school history teacher who strives to incorporate novel methods of information retrieval, data exploration, and human-computer interaction into their teaching method. The role demands creativity, adaptability, and an aptitude for technology. If you're curious, you might consider exploring how much does a high school history teacher make in North Dakota.

Other career opportunities within this field include data analysts, information architects, and user experience designers, among others. Each of these roles explores different facets of the topics discussed in the journal, thereby creating a diverse landscape of opportunities.

Top Publications

  • TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

    Unknown

    (2022)
    835 Citations
  • Deep entity matching with pre-trained language models

    Yuliang Li;Jinfeng Li;Yoshihiko Suhara;AnHai Doan

    (2020)
    499 Citations
  • Privacy preserving vertical federated learning for tree-based models

    Yuncheng Wu;Shaofeng Cai;Xiaokui Xiao;Gang Chen

    (2020)
    316 Citations
  • Plato: approximate analytics over compressed time series with tight deterministic error guarantees

    Chunbin Lin;Etienne Boursier;Yannis Papakonstantinou

    (2020)
    287 Citations
  • ATHENA++: natural language querying for complex nested SQL queries

    Jaydeep Sen;Chuan Lei;Abdul Quamar;Fatma Özcan

    (2020)
    234 Citations
  • DeepDB: learn from data, not from queries!

    Benjamin Hilprecht;Andreas Schmidt;Moritz Kulessa;Alejandro Molina

    (2020)
    220 Citations
  • The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds

    Paolo Ferragina;Giorgio Vinciguerra

    (2020)
    205 Citations
  • TiDB

    (2020)
    183 Citations
  • PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel

    Unknown

    (2023)
    182 Citations
  • Cloudburst: Stateful Functions-as-a-Service

    Vikram Sreekanti;Chenggang Wu;Xiayue Charles Lin;Johann Schleier-Smith

    (2020)
    164 Citations

Related Online Degrees & Career Pathways

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Ultimately, career outcomes matter. Pursuing degrees recognized among the highest paying degrees in the world can lead to lucrative roles and long-term financial stability in the competitive tech industry.

Best Scientists Contributing to This Journal