Matches in Ruben’s data for { <https://dx.doi.org/10.1109/ICSC.2016.55> ?p ?o }
- ICSC.2016.55 author wesley_de_neve.
- ICSC.2016.55 author tom_de_nies.
- ICSC.2016.55 author thomas_seidl.
- ICSC.2016.55 author stepien_grzegorz.
- ICSC.2016.55 author rik_van_de_walle.
- ICSC.2016.55 author laurens_de_vocht.
- ICSC.2016.55 author frederic_godin.
- ICSC.2016.55 author erik_mannens.
- ICSC.2016.55 author dorthe_arndt.
- ICSC.2016.55 author christian_beecks.
- ICSC.2016.55 author me.
- ICSC.2016.55 creator wesley_de_neve.
- ICSC.2016.55 creator tom_de_nies.
- ICSC.2016.55 creator thomas_seidl.
- ICSC.2016.55 creator stepien_grzegorz.
- ICSC.2016.55 creator rik_van_de_walle.
- ICSC.2016.55 creator laurens_de_vocht.
- ICSC.2016.55 creator frederic_godin.
- ICSC.2016.55 creator erik_mannens.
- ICSC.2016.55 creator dorthe_arndt.
- ICSC.2016.55 creator christian_beecks.
- ICSC.2016.55 creator me.
- ICSC.2016.55 about DBpedia.
- ICSC.2016.55 about Semantic_Web.
- ICSC.2016.55 about World_Wide_Web.
- ICSC.2016.55 author wesley_de_neve.
- ICSC.2016.55 author tom_de_nies.
- ICSC.2016.55 author thomas_seidl.
- ICSC.2016.55 author stepien_grzegorz.
- ICSC.2016.55 author rik_van_de_walle.
- ICSC.2016.55 author laurens_de_vocht.
- ICSC.2016.55 author frederic_godin.
- ICSC.2016.55 author erik_mannens.
- ICSC.2016.55 author dorthe_arndt.
- ICSC.2016.55 author christian_beecks.
- ICSC.2016.55 author me.
- ICSC.2016.55 coparticipatesWith wesley_de_neve.
- ICSC.2016.55 coparticipatesWith tom_de_nies.
- ICSC.2016.55 coparticipatesWith thomas_seidl.
- ICSC.2016.55 coparticipatesWith stepien_grzegorz.
- ICSC.2016.55 coparticipatesWith rik_van_de_walle.
- ICSC.2016.55 coparticipatesWith laurens_de_vocht.
- ICSC.2016.55 coparticipatesWith frederic_godin.
- ICSC.2016.55 coparticipatesWith erik_mannens.
- ICSC.2016.55 coparticipatesWith dorthe_arndt.
- ICSC.2016.55 coparticipatesWith christian_beecks.
- ICSC.2016.55 coparticipatesWith me.
- ICSC.2016.55 type ScholarlyArticle.
- ICSC.2016.55 type Article.
- ICSC.2016.55 type Document.
- ICSC.2016.55 type Document.
- ICSC.2016.55 type Document.
- ICSC.2016.55 type Q386724.
- ICSC.2016.55 type CreativeWork.
- ICSC.2016.55 type Work.
- ICSC.2016.55 P50 wesley_de_neve.
- ICSC.2016.55 P50 tom_de_nies.
- ICSC.2016.55 P50 thomas_seidl.
- ICSC.2016.55 P50 stepien_grzegorz.
- ICSC.2016.55 P50 rik_van_de_walle.
- ICSC.2016.55 P50 laurens_de_vocht.
- ICSC.2016.55 P50 frederic_godin.
- ICSC.2016.55 P50 erik_mannens.
- ICSC.2016.55 P50 dorthe_arndt.
- ICSC.2016.55 P50 christian_beecks.
- ICSC.2016.55 P50 me.
- ICSC.2016.55 maker wesley_de_neve.
- ICSC.2016.55 maker tom_de_nies.
- ICSC.2016.55 maker thomas_seidl.
- ICSC.2016.55 maker stepien_grzegorz.
- ICSC.2016.55 maker rik_van_de_walle.
- ICSC.2016.55 maker laurens_de_vocht.
- ICSC.2016.55 maker frederic_godin.
- ICSC.2016.55 maker erik_mannens.
- ICSC.2016.55 maker dorthe_arndt.
- ICSC.2016.55 maker christian_beecks.
- ICSC.2016.55 maker me.
- ICSC.2016.55 title "Distance-based Approach for Semantic Dissimilarity in Knowledge Graphs".
- ICSC.2016.55 isPartOf proceedings_of_the_10th_international_conference_on_semantic_computing.
- ICSC.2016.55 name "Distance-based Approach for Semantic Dissimilarity in Knowledge Graphs".
- ICSC.2016.55 label "Distance-based Approach for Semantic Dissimilarity in Knowledge Graphs".
- ICSC.2016.55 name "Distance-based Approach for Semantic Dissimilarity in Knowledge Graphs".
- ICSC.2016.55 topic DBpedia.
- ICSC.2016.55 topic Semantic_Web.
- ICSC.2016.55 topic World_Wide_Web.
- ICSC.2016.55 subject DBpedia.
- ICSC.2016.55 subject Semantic_Web.
- ICSC.2016.55 subject World_Wide_Web.
- ICSC.2016.55 authorList b0_b2636.
- ICSC.2016.55 topic DBpedia.
- ICSC.2016.55 topic Semantic_Web.
- ICSC.2016.55 topic World_Wide_Web.
- ICSC.2016.55 abstract "In this paper, we propose and investigate a novel distance-based approach for measuring the semantic dissimilarity between two concepts in a knowledge graph. The proposed Normalized Semantic Web Distance (NSWD) extends the idea of the Normalized Web Distance, which is utilized to determine the dissimilarity between two textural terms, and utilizes additional semantic properties of nodes in a knowledge graph. We evaluate our proposal on two different knowledge graphs: Freebase and DBpedia. While the NSWD achieves a correlation of up to 0.58 with human similarity assessments on the established Miller-Charles benchmark of 30 term-pairs on the Freebase knowledge graph, it reaches an even higher correlation of 0.69 in the DBpedia knowledge graph. We thus conclude that the proposed NSWD is an efficient and effective distance-based approach for assessing semantic dissimilarity in very large knowledge graphs.".
- ICSC.2016.55 datePublished "2016".
- ICSC.2016.55 mainEntityOfPage denies_icsc_2016.
- ICSC.2016.55 sameAs ICSC.2016.55.
- ICSC.2016.55 isPrimaryTopicOf denies_icsc_2016.
- ICSC.2016.55 page denies_icsc_2016.
- ICSC.2016.55 number "254".
- ICSC.2016.55 number "257".