Treffer: Comparison of mean interconcept distance for embedding with WordNet synonym replacement (WN) and without (PM). The initial number of unique concepts in the total corpus was 3,018,918. The Table summarizes results for different thresholds () and categories of concept/gene sets (M,B,K,G,P). Columns: : Replacement threshold; replaced: Unique Replaced Concepts; Category: M = MeSH, B = Biocarta, K = KEGG, G = GP(bp), P = PID; # sets: Number of concept/gene sets in the categories; #Concepts: number of concept vectors in the category; WN better : The count and percentage of concept/gene sets for which the mean interconcept distance was smaller for WN than for PM. “Winners” are shown in bold.; PM better : Analogous to “WN better” but for PM.
Title:
Comparison of mean interconcept distance for embedding with WordNet synonym replacement (WN) and without (PM). The initial number of unique concepts in the total corpus was 3,018,918. The Table summarizes results for different thresholds () and categories of concept/gene sets (M,B,K,G,P). Columns: : Replacement threshold; replaced: Unique Replaced Concepts; Category: M = MeSH, B = Biocarta, K = KEGG, G = GP(bp), P = PID; # sets: Number of concept/gene sets in the categories; #Concepts: number of concept vectors in the category; WN better : The count and percentage of concept/gene sets for which the mean interconcept distance was smaller for WN than for PM. “Winners” are shown in bold.; PM better : Analogous to “WN better” but for PM.
Authors:
Publication Year:
2025
Subject Terms:
Cancer, Science Policy, Space Science, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Information Systems not elsewhere classified, semantically meaningful representations, received less attention, python code implementing, ensuring consistent representation, combined approach aimed, cell lung carcinoma, additionally leveraged wordnet, 8 %, suggesting, reduce embedding noise, improving embedding quality, higher embedding quality, biomedical synonym replacement, biomedical concept representations, +embeddings%22">xlink "> embeddings, word2vec algorithm applied, span multiple words, mean pairwise distance, single concept identifier, biomedical concept synonyms, embedding techniques, biomedical terms, biomedical synonyms
Document Type:
dataset
Language:
unknown
DOI:
10.1371/journal.pone.0322498.t001
Availability:
https://doi.org/10.1371/journal.pone.0322498.t001
https://figshare.com/articles/dataset/Comparison_of_mean_interconcept_distance_for_embedding_with_WordNet_synonym_replacement_WN_and_without_PM_The_initial_number_of_unique_concepts_in_the_total_corpus_was_3_018_918_The_Table_summarizes_results_for_different_thresholds_and_cate/28933845
https://figshare.com/articles/dataset/Comparison_of_mean_interconcept_distance_for_embedding_with_WordNet_synonym_replacement_WN_and_without_PM_The_initial_number_of_unique_concepts_in_the_total_corpus_was_3_018_918_The_Table_summarizes_results_for_different_thresholds_and_cate/28933845
Rights:
CC BY 4.0
Accession Number:
edsbas.983CF9ED
Database:
BASE
Weitere Informationen
Comparison of mean interconcept distance for embedding with WordNet synonym replacement (WN) and without (PM). The initial number of unique concepts in the total corpus was 3,018,918. The Table summarizes results for different thresholds () and categories of concept/gene sets (M,B,K,G,P). Columns: : Replacement threshold; replaced: Unique Replaced Concepts; Category: M = MeSH, B = Biocarta, K = KEGG, G = GP(bp), P = PID; # sets: Number of concept/gene sets in the categories; #Concepts: number of concept vectors in the category; WN better : The count and percentage of concept/gene sets for which the mean interconcept distance was smaller for WN than for PM. “Winners” are shown in bold.; PM better : Analogous to “WN better” but for PM.