SOTAVerified

Keyword Extraction

Keyword extraction is tasked with the automatic identification of terms that best describe the subject of a document (Source: Wikipedia).

Papers

Showing 76–100 of 172 papers

TitleStatusHype
Theme-weighted Ranking of Keywords from Text Documents using Phrase Embeddings—0
Thesis: Document Summarization with applications to Keyword extraction and Image Retrieval—0
Tools for Arabic Natural Language Processing: a case study in qalqalah prosody—0
Toward Network-based Keyword Extraction from Multitopic Web Documents—0
Towards Automatic Description of Knowledge Components—0
Toward Selectivity Based Keyword Extraction for Croatian News—0
Towards Mapping Thesauri onto plWordNet—0
Two baselines for unsupervised dependency parsing—0
UNIMIB at TREC 2021 Clinical Trials Track—0
Unsupervised Approach for Automatic Keyword Extraction from Arabic Documents—0
Unsupervised Keyword Extraction for Full-sentence VQA—0
Unsupervised Keyword Extraction from Polish Legal Texts—0
Unsupervised Learning Algorithms for Keyword Extraction in an Undergraduate Thesis—0
Urania: Differentially Private Insights into AI Use—0
Using virtual edges to extract keywords from texts modeled as complex networks—0
Using Zero-shot Prompting in the Automatic Creation and Expansion of Topic Taxonomies for Tagging Retail Banking Transactions—0
VisualTextRank: Unsupervised Graph-based Content Extraction for Automating Ad Text to Image Search—0
What Is a Good Caption? A Comprehensive Visual Caption Benchmark for Evaluating Both Correctness and Thoroughness—0
Word Embedding Neural Networks to Advance Knee Osteoarthritis Research—0
专业技术文本关键词抽取方法(Keyword Extraction on Professional Technical Text)—0
Improving Performance of Automatic Keyword Extraction (AKE) Methods Using PoS-Tagging and Enhanced Semantic-Awareness—0
Interest Analysis using PageRank and Social Interaction Content—0
JobHam-place with smart recommend job options and candidate filtering options—0
Joint Learning of Chinese Words, Terms and Keywords—0
Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving—0
Show:102550
← PrevPage 4 of 7Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Phraseformer(BERT, ExEm(ft))F1 score69.87—Unverified
2Phraseformer(BERT, ExEm(w2v))F1 score69.7—Unverified
3Phraseformer(BERT, Node2vec)F1 score68.68—Unverified
4Phraseformer(BERT, DeepWalk)F1 score68.44—Unverified
5FRAKEF1 score58.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Phraseformer(BERT, ExEm(ft))F1 score48.65—Unverified
2Phraseformer(BERT, ExEm(w2v))F1 score48.48—Unverified
3Phraseformer(BERT, Node2vec)F1 score47.46—Unverified
4Phraseformer(BERT, DeepWalk)F1 score47.22—Unverified
5FRAKEF1 score37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1Phraseformer(BERT, ExEm(ft))F1 score67.13—Unverified
2Phraseformer(BERT, ExEm(w2v))F1 score66.96—Unverified
3Phraseformer(BERT, Node2vec)F1 score65.94—Unverified
4Phraseformer(BERT, DeepWalk)F1 score65.7—Unverified
5FRAKEF1 score54—Unverified