Top 20 Keyword Pairs from Combined Eigenvector Centrality and Word2Vec Models

Top 20 keyword pairs extracted from combined models using eigenvector centrality and Word2Vec. The dataset is a 9.5 KB XLS file authored by Jin Gyeong Kim and shared under a CC-BY-4.0 license on figshare. It was last updated on May 8, 2026.

Use Cases

• Analyze keyword co-occurrence and semantic relationships based on the combined eigenvector centrality and Word2Vec methodology.
• Validate or compare keyword extraction algorithms based on the top-ranking pairs.
• Use the ranked keyword pairs as a benchmark or seed set for downstream text mining tasks.

Strengths

• Dataset is openly licensed (CC-BY-4.0), permitting reuse and modification.
• File size is 9.5 KB, indicating a lightweight and easily accessible resource.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Extracted from combined models using eigenvector centrality and Word2Vec.

Time Range

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Freshness

Last updated 2026-05-08 17:23:32; freshness should be verified.

Geography

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