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Expressing structural hypertext queries in graphlog

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A. O. MendelzonAuthors Info & Claims

HYPERTEXT '89: Proceedings of the second annual ACM conference on Hypertext

Pages 269 - 292

https://doi.org/10.1145/74224.74247

Published: 01 November 1989 Publication History

Abstract

GraphLog is a visual query language in which queries are formulated by drawing graph patterns. The hyperdocument graph is searched for all occurrences of these patterns. The language is powerful enough to allow the specification and manipulation of arbitrary subsets of the network and supports the computation of aggregate functions on subgraphs of the hyperdocument. It can support dynamically defined structures as well as inference capabilities, going beyond current static and passive hypertext systems.

The expressive power of the language is a fundamental issue: too little power limits the applications of the language, while too much makes efficient implementation difficult and probably affects ease of use. The complexity and expressive power of GraphLog can be characterized precisely by using notions from deductive database theory and descriptive complexity. In this paper, from a practical point of view, we present examples of GraphLog queries applied to several different hypertext systems, providing evidence for the expressive power of the language, as well as for the convenience and naturalness of its graphical representation. We also describe an ongoing implementation of the language.

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Cited By

Li YRadev DRafiei DLi YRadev DRafiei D(2023)Data and Query ModelNatural Language Interfaces to Databases10.1007/978-3-031-45043-3_3(27-47)Online publication date: 25-Nov-2023
https://doi.org/10.1007/978-3-031-45043-3_3
Kyriakidi MKoutrika GIoannidis Y(2020)Recommendations as Graph ExplorationsProceedings of the 14th ACM Conference on Recommender Systems10.1145/3383313.3412269(289-298)Online publication date: 22-Sep-2020
https://dl.acm.org/doi/10.1145/3383313.3412269
Kyriakidi MKoutrika GIoannidis Y(2018)Recommendations for Explorations based on GraphsProceedings of the 5th International Workshop on Exploratory Search in Databases and the Web10.1145/3214708.3214713(1-4)Online publication date: 15-Jun-2018
https://dl.acm.org/doi/10.1145/3214708.3214713
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Index Terms

Expressing structural hypertext queries in graphlog
1. Computing methodologies
  1. Computer graphics
2. Information systems

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cover image ACM Conferences

HYPERTEXT '89: Proceedings of the second annual ACM conference on Hypertext

November 1989

403 pages

ISBN:0897913396

DOI:10.1145/74224

Chairman:
R. Akscyn

Copyright © 1989 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 ACM 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]

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Published: 01 November 1989

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Cited By

Li YRadev DRafiei DLi YRadev DRafiei D(2023)Data and Query ModelNatural Language Interfaces to Databases10.1007/978-3-031-45043-3_3(27-47)Online publication date: 25-Nov-2023
https://doi.org/10.1007/978-3-031-45043-3_3
Kyriakidi MKoutrika GIoannidis Y(2020)Recommendations as Graph ExplorationsProceedings of the 14th ACM Conference on Recommender Systems10.1145/3383313.3412269(289-298)Online publication date: 22-Sep-2020
https://dl.acm.org/doi/10.1145/3383313.3412269
Kyriakidi MKoutrika GIoannidis Y(2018)Recommendations for Explorations based on GraphsProceedings of the 5th International Workshop on Exploratory Search in Databases and the Web10.1145/3214708.3214713(1-4)Online publication date: 15-Jun-2018
https://dl.acm.org/doi/10.1145/3214708.3214713
Poulovassilis A(2018)Applications of Flexible Querying to Graph DataGraph Data Management10.1007/978-3-319-96193-4_4(97-142)Online publication date: 1-Nov-2018
https://doi.org/10.1007/978-3-319-96193-4_4
Marx MKrötzsch MThost V(2017)Logic on MARSProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171642.3171811(1188-1194)Online publication date: 19-Aug-2017
https://dl.acm.org/doi/10.5555/3171642.3171811
Yang YPintus RGobbetti ERushmeier H(2017)Automatic Single Page-Based Algorithms for Medieval Manuscript AnalysisJournal on Computing and Cultural Heritage 10.1145/299646910:2(1-22)Online publication date: 21-Mar-2017
https://dl.acm.org/doi/10.1145/2996469
Khan ARanu S(2017)Big-Graphs: Querying, Mining, and BeyondHandbook of Big Data Technologies10.1007/978-3-319-49340-4_16(531-582)Online publication date: 26-Feb-2017
https://doi.org/10.1007/978-3-319-49340-4_16
van Rest OHong SKim JMeng XChafi H(2016)PGQLProceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems10.1145/2960414.2960421(1-6)Online publication date: 24-Jun-2016
https://dl.acm.org/doi/10.1145/2960414.2960421
(2016)Approximation and relaxation of semantic web path queriesWeb Semantics: Science, Services and Agents on the World Wide Web10.1016/j.websem.2016.08.00140:C(1-21)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.websem.2016.08.001
Yordanova KKirste T(2015)A Process for Systematic Development of Symbolic Models for Activity RecognitionACM Transactions on Interactive Intelligent Systems10.1145/28068935:4(1-35)Online publication date: 22-Dec-2015
https://dl.acm.org/doi/10.1145/2806893
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