Contextualized ranking of entity types based on knowledge graphs-Reference-Cited by-同舟云学术

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Contextualized ranking of entity types based on knowledge graphs

Published:2016-03 Issue: Volume:37-38 Page:170-183
ISSN:1570-8268
Container-title:Journal of Web Semantics
language:en
Short-container-title:Journal of Web Semantics

Author:

Tonon Alberto^ORCID,Catasta Michele,Prokofyev Roman,Demartini Gianluca,Aberer Karl,Cudré-Mauroux Philippe

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Human-Computer Interaction,Software

Reference43 articles.

1. A characterization of online search behavior;Kumar;IEEE Data Eng. Bull.,2009

2. Ad-hoc object retrieval in the web of data;Pound,2010

3. Combining inverted indices and structured search for ad-hoc object retrieval;Tonon,2012

4. Yago: a core of semantic knowledge;Suchanek,2007

5. A. Tonon, M. Catasta, G. Demartini, P. Cudré-Mauroux, K. Aberer, TRank: Ranking entity types using the web of data, in: Lecture Notes in Computer Science, LNCS, Vol. 8218, 2013, pp. 640–656.

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1. Construction of Knowledge Graphs: Current State and Challenges;2023

2. Extracting data models from background knowledge graphs;Knowledge-Based Systems;2022-02

3. Customer transactional behaviour analysis through embedding interpretation;Procedia Computer Science;2022

4. ESDL: Entity Summarization with Deep Learning;Proceedings of the 10th International Joint Conference on Knowledge Graphs;2021-12-06

5. A Review of Graph-Based Models for Entity-Oriented Search;SN Computer Science;2021-08-30

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