WebKnoGraph/CITATION.cff at main · martech-engineer/WebKnoGraph · GitHub

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# This CITATION.cff file was generated and enriched for completeness
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
type: software
title: "WebKnoGraph"
abstract: >-
  WebKnoGraph is an open research project that uses data processing,
  vector embeddings, and graph algorithms to optimize internal linking
  at scale. Built for both academic and industry use, it offers the first
  fully transparent, AI-driven framework for improving SEO and site
  navigation through reproducible methods. The project revolutionizes
  website internal linking by leveraging cutting-edge data processing
  techniques, vector embeddings, and graph-based link prediction algorithms.
authors:
  - family-names: "Gjorgjevska"
    given-names: "Emilija"
    affiliation: "Independent Researcher"
    website: "https://www.linkedin.com/in/emilijagjorgjevska/"
  - family-names: "Mirceva"
    given-names: "Georgina"
    affiliation: "Faculty of Computer Science and Engineering (FCSE), Skopje"
  - family-names: "Mirchev"
    given-names: "Miroslav"
    affiliation: "Faculty of Computer Science and Engineering (FCSE), Skopje"
keywords:
  - "SEO"
  - "internal linking"
  - "graph algorithms"
  - "vector embeddings"
  - "artificial intelligence"
  - "web optimization"
  - "link prediction"
  - "GraphSAGE"
  - "PageRank"
  - "HITS algorithm"
  - "marketing technology"
  - "content optimization"
license: "Apache-2.0"
url: "https://github.com/martech-engineer/WebKnoGraph"
repository-code: "https://github.com/martech-engineer/WebKnoGraph"
sponsors:
  - name: "WordLift"
    url: "https://wordlift.io"
  - name: "Faculty of Computer Science and Engineering (FCSE), Skopje"
    url: "https://www.finki.ukim.mk"
  - name: "Kalicube"
    url: "https://kalicube.com"
# version: "1.0.0"  # Uncomment and update when you tag a release
# date-released: "2024-12-01"  # Uncomment and update with actual release date
# doi: "10.5281/zenodo.XXXXXXX"  # Uncomment and add DOI when available
preferred-citation:
  type: software
  title: "WebKnoGraph: AI-Driven Framework for Large-Scale Internal Link Optimization"
  authors:
    - family-names: "Gjorgjevska"
      given-names: "Emilija"
    - family-names: "Mirceva"
      given-names: "Georgina"
    - family-names: "Mirchev"
      given-names: "Miroslav"
  year: 2024
  url: "https://github.com/martech-engineer/WebKnoGraph"
  abstract: >-
    WebKnoGraph presents the first fully transparent, AI-driven framework
    for optimizing internal linking structures at scale. The system combines
    advanced data processing techniques, vector embeddings, and graph-based
    algorithms to enhance SEO performance and user navigation through
    reproducible, scientific methods.