article

Summarizing answer graphs induced by keyword queries

Authors:

Mudhakar Srivatsa,

Xifeng YanAuthors Info & Claims

Proceedings of the VLDB Endowment, Volume 6, Issue 14

Pages 1774 - 1785

https://doi.org/10.14778/2556549.2556561

Published: 01 September 2013 Publication History

Abstract

Keyword search has been popularly used to query graph data. Due to the lack of structure support, a keyword query might generate an excessive number of matches, referred to as "answer graphs", that could include different relationships among keywords. An ignored yet important task is to group and summarize answer graphs that share similar structures and contents for better query interpretation and result understanding. This paper studies the summarization problem for the answer graphs induced by a keyword query Q. (1) A notion of summary graph is proposed to characterize the summarization of answer graphs. Given Q and a set of answer graphs G, a summary graph preserves the relation of the keywords in Q by summarizing the paths connecting the keywords nodes in G. (2) A quality metric of summary graphs, called coverage ratio, is developed to measure information loss of summarization. (3) Based on the metric, a set of summarization problems are formulated, which aim to find minimized summary graphs with certain coverage ratio. (a) We show that the complexity of these summarization problems ranges from ptime to NP-complete. (b) We provide exact and heuristic summarization algorithms. (4) Using real-life and synthetic graphs, we experimentally verify the effectiveness and the efficiency of our techniques.

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Yang SYang ZChen XZhao JMa Y(2021)Distributed aggregation-based attributed graph summarization for summary-based approximate attributed graph queriesExpert Systems with Applications: An International Journal10.1016/j.eswa.2021.114921176:COnline publication date: 15-Aug-2021
https://dl.acm.org/doi/10.1016/j.eswa.2021.114921
Ashrafi-Payaman NKangavari MHosseini SFander A(2021)GS4: Graph stream summarization based on both the structure and semanticsThe Journal of Supercomputing10.1007/s11227-020-03290-277:3(2713-2733)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1007/s11227-020-03290-2
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cover image Proceedings of the VLDB Endowment

Proceedings of the VLDB Endowment Volume 6, Issue 14

September 2013

384 pages

ISSN:2150-8097

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VLDB Endowment

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Published: 01 September 2013

Published in PVLDB Volume 6, Issue 14

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Cited By

Ke XKhan ABonchi F(2022)Multi-relation Graph SummarizationACM Transactions on Knowledge Discovery from Data10.1145/349456116:5(1-30)Online publication date: 9-Mar-2022
https://dl.acm.org/doi/10.1145/3494561
Yang SYang ZChen XZhao JMa Y(2021)Distributed aggregation-based attributed graph summarization for summary-based approximate attributed graph queriesExpert Systems with Applications: An International Journal10.1016/j.eswa.2021.114921176:COnline publication date: 15-Aug-2021
https://dl.acm.org/doi/10.1016/j.eswa.2021.114921
Ashrafi-Payaman NKangavari MHosseini SFander A(2021)GS4: Graph stream summarization based on both the structure and semanticsThe Journal of Supercomputing10.1007/s11227-020-03290-277:3(2713-2733)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1007/s11227-020-03290-2
Belth CZheng XVreeken JKoutra D(2020)What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive SummarizationProceedings of The Web Conference 202010.1145/3366423.3380189(1115-1126)Online publication date: 20-Apr-2020
https://dl.acm.org/doi/10.1145/3366423.3380189
Witschel HRiesen KGrether L(2020)KvGR: A Graph-Based Interface for Explorative Sequential Question Answering on Heterogeneous Information SourcesAdvances in Information Retrieval10.1007/978-3-030-45439-5_50(760-773)Online publication date: 14-Apr-2020
https://dl.acm.org/doi/10.1007/978-3-030-45439-5_50
Mohanty MRamanath MRanu SGanguly NRamakrishnan RSarawagi SRoy S(2018)KlustreeProceedings of the ACM India Joint International Conference on Data Science and Management of Data10.1145/3152494.3152509(265-272)Online publication date: 11-Jan-2018
https://dl.acm.org/doi/10.1145/3152494.3152509
Zhong MWang YZhu Y(2018)Coverage-Oriented Diversification of Keyword Search Results on GraphsDatabase Systems for Advanced Applications10.1007/978-3-319-91458-9_10(166-183)Online publication date: 21-May-2018
https://dl.acm.org/doi/10.1007/978-3-319-91458-9_10
Khan ABhowmick SBonchi F(2017)Summarizing static and dynamic big graphsProceedings of the VLDB Endowment10.14778/3137765.313782510:12(1981-1984)Online publication date: 1-Aug-2017
https://dl.acm.org/doi/10.14778/3137765.3137825
Mottin DMüller EChirkova RYang JSuciu D(2017)Graph ExplorationProceedings of the 2017 ACM International Conference on Management of Data10.1145/3035918.3054778(1737-1740)Online publication date: 9-May-2017
https://dl.acm.org/doi/10.1145/3035918.3054778
Bhowmick SChoi BLi CChirkova RYang JSuciu D(2017)Graph Querying Meets HCIProceedings of the 2017 ACM International Conference on Management of Data10.1145/3035918.3054774(1731-1736)Online publication date: 9-May-2017
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