research-article

DBtrends: Exploring Query Logs for Ranking RDF Data

Authors:

Amrapali Zaveri,

Diego Moussallem,

Sandro RautenbergAuthors Info & Claims

SEMANTiCS 2016: Proceedings of the 12th International Conference on Semantic Systems

Pages 9 - 16

https://doi.org/10.1145/2993318.2993322

Published: 12 September 2016 Publication History

Abstract

Many ranking methods have been proposed for RDF data. These methods often use the structure behind the data to measure its importance. Recently, some of these methods have started to explore information from other sources such as the Wikipedia page graph for better ranking RDF data. In this work, we propose DBtrends, a ranking function based on query logs. We extensively evaluate the application of different ranking functions for entities, classes, and properties across two different countries as well as their combination. Thereafter, we propose MIXED-RANK, a ranking function that combines DBtrends with the best-evaluated entity ranking function. We show that: (i) MIXED-RANK outperforms state-of-the-art entity ranking functions, and; (ii) query logs can be used to improve RDF ranking functions.

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Cited By

Marx EValdestilhas ABeck HSoru T(2021)SANTé: A Light-Weight End-to-End Semantic Search Framework for RDF DataThe Semantic Web: ESWC 2021 Satellite Events10.1007/978-3-030-80418-3_17(93-97)Online publication date: 21-Jul-2021
https://doi.org/10.1007/978-3-030-80418-3_17
Desouki ARöder MNgonga Ngomo AAtzenbeck CRubart JMillard D(2019)Ranking on Very Large Knowledge GraphsProceedings of the 30th ACM Conference on Hypertext and Social Media10.1145/3342220.3343660(163-171)Online publication date: 12-Sep-2019
https://dl.acm.org/doi/10.1145/3342220.3343660
Sakthi Murugan RAnanthanarayana V(2019)NPRank: Nexus based Predicate Ranking of Linked Data2019 International Conference on Data Science and Engineering (ICDSE)10.1109/ICDSE47409.2019.8971791(46-50)Online publication date: Sep-2019
https://doi.org/10.1109/ICDSE47409.2019.8971791
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Published In

cover image ACM Other conferences

SEMANTiCS 2016: Proceedings of the 12th International Conference on Semantic Systems

September 2016

207 pages

ISBN:9781450347525

DOI:10.1145/2993318

Editors:
Anna Fensel
STI Innsbruck, University of Innsbruck, Austria
,
Amrapali Zaveri
Stanford University, USA
,
Sebastian Hellmann
AKSW/KILT, Institute for Applied Informatics (InfAI), Leipzig, Germany
,
Tassilo Pellegrini
University of Applied Sciences St. Poelten, Austria

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

In-Cooperation

Ghent University: Ghent University
AIT: Austrian Institute of Technology
Stanford University: Stanford University
Wolters Kluwer: Wolters Kluwer, Germany
Semantic Web Company: Semantic Web Company

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 September 2016

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Conselho Nacional de Desenvolvimento Científico e Tecnológico

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SEMANTiCS 2016

SEMANTiCS 2016: 12th International Conference on Semantic Systems

September 12 - 15, 2016

Leipzig, Germany

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SEMANTiCS 2016 Paper Acceptance Rate 18 of 85 submissions, 21%;

Overall Acceptance Rate 40 of 182 submissions, 22%

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Cited By

Marx EValdestilhas ABeck HSoru T(2021)SANTé: A Light-Weight End-to-End Semantic Search Framework for RDF DataThe Semantic Web: ESWC 2021 Satellite Events10.1007/978-3-030-80418-3_17(93-97)Online publication date: 21-Jul-2021
https://doi.org/10.1007/978-3-030-80418-3_17
Desouki ARöder MNgonga Ngomo AAtzenbeck CRubart JMillard D(2019)Ranking on Very Large Knowledge GraphsProceedings of the 30th ACM Conference on Hypertext and Social Media10.1145/3342220.3343660(163-171)Online publication date: 12-Sep-2019
https://dl.acm.org/doi/10.1145/3342220.3343660
Sakthi Murugan RAnanthanarayana V(2019)NPRank: Nexus based Predicate Ranking of Linked Data2019 International Conference on Data Science and Engineering (ICDSE)10.1109/ICDSE47409.2019.8971791(46-50)Online publication date: Sep-2019
https://doi.org/10.1109/ICDSE47409.2019.8971791
Marx EPublio GRiechert T(2019)CACAO: Conditional Spread Activation for Keyword Factual Query InterpretationSemantic Systems. The Power of AI and Knowledge Graphs10.1007/978-3-030-33220-4_19(256-271)Online publication date: 4-Nov-2019
https://doi.org/10.1007/978-3-030-33220-4_19
Menendez ECasanova MPaes Leme LBoughanem M(2019)Novel Node Importance Measures to Improve Keyword Search over RDF GraphsDatabase and Expert Systems Applications10.1007/978-3-030-27618-8_11(143-158)Online publication date: 6-Aug-2019
https://doi.org/10.1007/978-3-030-27618-8_11
Khouri SLanasri DSaidoune RBoudoukha KBellatreche L(2019)LogLInc: LoG Queries of Linked Open Data Investigator for Cube DesignDatabase and Expert Systems Applications10.1007/978-3-030-27615-7_27(352-367)Online publication date: 3-Aug-2019
https://doi.org/10.1007/978-3-030-27615-7_27
Degbelo A(2017)Linked Data and VisualizationProceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics10.1145/3152178.3152191(1-8)Online publication date: 7-Nov-2017
https://dl.acm.org/doi/10.1145/3152178.3152191
Ermilov TMoussallem DUsbeck RNgomo ASheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)GENESISProceedings of the International Conference on Web Intelligence10.1145/3106426.3106514(125-131)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3106514

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