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    Machine Learning and Knowledge Extraction

    Machine Learning and Knowledge Extraction is Scopus-indexed (Q1, CiteScore 12.7), WoS ESCI, DOAJ. Published by Multidisciplinary Digital Publishing Institute (MDPI).

    Checked against the index lists dated 4 October 2026.

    ISSN 2504-4990Verify ISSN ↗

    Publisher: Multidisciplinary Digital Publishing Institute (MDPI)

    Scopus · Q1WoS · ESCIOpen Access
    12.7
    CiteScore 2025
    Scopus
    Q1
    Best quartile
    rank 22 of 300 · 92nd pctile
    3
    Indexed in
    major indexes

    Cost to publish: Checking DOAJ for article charges…

    ScopusElsevier Scopus
    Status
    Active
    Coverage
    2019–present
    Source type
    Journal
    Open access
    Yes
    CiteScore
    12.7
    SJR · SCImago
    1.548
    Q1 SJR quartile
    H-index
    46
    Best quartile
    Q1 · 92nd pctile
    Subject areaRankPctileQ
    Engineering (miscellaneous)22 / 30092ndQ1
    Artificial Intelligence59 / 57089thQ1
    View this source on Scopus.com
    Web of ScienceClarivate (SCIE/SSCI/AHCI/ESCI)
    Collections
    ESCI
    Categories
    Computer Science, Artificial IntelligenceComputer Science, Interdisciplinary ApplicationsEngineering, Electrical & Electronic
    View this source on Web of Science Check JIF in JCR
    DOAJDirectory of Open Access Journals (live)
    Listed in DOAJ
    Open accessFully open access, peer reviewed

    Not listed in: ABDC, ABS / AJG, FT50, UT Dallas, ONOS (subscription), ONOS (APC covered)

    Quick answers

    Is Machine Learning and Knowledge Extraction indexed in Scopus?

    Yes — actively indexed in Scopus, coverage 2019–present, best quartile Q1, CiteScore 12.7.

    What quartile is Machine Learning and Knowledge Extraction in Scopus?

    Machine Learning and Knowledge Extraction is Q1 in Engineering (miscellaneous) (rank 22 of 300) and Q1 in Artificial Intelligence (rank 59 of 570), by CiteScore 2025.

    What is the impact factor of Machine Learning and Knowledge Extraction?

    Machine Learning and Knowledge Extraction is indexed in the Emerging Sources Citation Index, so it may have a Journal Impact Factor in Clarivate's Journal Citation Reports. JCR is paid, so check it for the current value. The closest free measure is its Scopus CiteScore 12.7, which places it in quartile Q1 at the 92nd percentile of its subject. Its SCImago Journal Rank (SJR, a free Scopus-based metric) is 1.548, quartile Q1, with an H-index of 46.

    How much does it cost to publish in Machine Learning and Knowledge Extraction?

    The publisher lists an article processing charge of about US$2,172 for open access (source: OpenAlex). Many journals also publish by the subscription route at no cost to the author, so confirm on the journal's own website.

    Who publishes Machine Learning and Knowledge Extraction and what is its ISSN?

    Machine Learning and Knowledge Extraction is published by Multidisciplinary Digital Publishing Institute (MDPI). Its ISSN is 2504-4990.

    Is Machine Learning and Knowledge Extraction in Web of Science?

    Yes — indexed in the Emerging Sources Citation Index.

    Is Machine Learning and Knowledge Extraction open access?

    Yes — it is an open-access journal, listed in DOAJ.

    How well cited is Machine Learning and Knowledge Extraction? — open metrics via OpenAlex

    Machine Learning and Knowledge Extraction has an h-index of 52 and a 2-year mean of 5.38 citations per paper (OpenAlex). Its Scopus CiteScore is 12.7, quartile Q1. On 2-year citations it ranks #33 of 268 Scopus journals in Engineering (miscellaneous).

    52
    h-index
    5.38
    2-yr mean citations
    246
    i10-index
    902
    works indexed
    15,162
    total citations
    Publication fee · open access list price, US$
    US$2,172
    05001,0002,0003,000+
    2-yr mean citations, among Scopus journals in the same subject
    #33 of 268 Top 13% Engineering (miscellaneous)
    #89 of 407 Top 22% Artificial Intelligence
    Papers published per year
    02505002017: 2 papers220172018: 15 papers1520182019: 45 papers4520192020: 40 papers4020202021: 48 papers4820212022: 58 papers5820222023: 95 papers9520232024: 139 papers13920242025: 175 papers17520252026: 285 papers so far2852026*

    Machine Learning and Knowledge Extraction published 175 papers in 2025. 2026* is the year so far.

    Main topics
    Explainable Artificial Intelligence (XAI)Topic ModelingAdversarial Robustness in Machine LearningAdvanced Neural Network Applications

    h-index, i10-index and 2-year mean citedness are open, licence-clear metrics from OpenAlex — not a proprietary impact factor. The subject rank counts only journals that OpenAlex has a figure for; it is not a Scopus or Clarivate ranking. Updated 2026-10-14.

    Who publishes in Machine Learning and Knowledge Extraction? — latest 98 articles, 2026

    In its latest 98 research articles (2026), authors are most often from China (8.2%), United States (7.1%) and Spain (7.1%).

    Author countriesChinaChina8.2%United StatesUnited States7.1%SpainSpain7.1%MexicoMexico6.6%RussiaRussia5.1%KazakhstanKazakhstan4.9% Most frequent institutions (papers)Multimedia UniversityMultimedia University4Al-Farabi Kazakh National UniversityAl-Farabi Kazakh National Unive…3Singidunum UniversitySingidunum University2University SinergijaUniversity Sinergija2Universitatea Națională de Știință și Tehnologie Politehnica BucureștiUniversitatea Națională de Știi…2

    Countries are counted fractionally, so a paper by authors from two countries counts half to each.

    Are there integrity warnings for Machine Learning and Knowledge Extraction? — indicators, not proof of misconduct

    Scopus status: Active. No retracted papers are recorded. The Problematic Paper Screener flags none of its papers. These are indicators to check, not findings against the journal.

    • Scopus statusActive
    • Retracted papers None recorded
    • Problematic Paper Screener flags None flagged

    Retractions from OpenAlex; flags from the Problematic Paper Screener (Cabanac, Labbé & Magazinov, CC BY), 2026-09-21 export. A flag marks a paper for a closer look; it is not a finding against the journal.

    Official sources & links

    Journal website ↗ Scopus source ↗ Web of Science ↗ DOAJ ↗ ISSN Portal · 2504-4990 ↗

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