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EVIN: building a knowledge base of events

Authors:

Erdal Kuzey,

Gerhard WeikumAuthors Info & Claims

WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web

Pages 103 - 106

https://doi.org/10.1145/2567948.2577009

Published: 07 April 2014 Publication History

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Abstract

We present EVIN: a system that extracts named events from news articles, reconciles them into canonicalized events, and organizes them into semantic classes to populate a knowledge base. EVIN exploits different kinds of similarity measures among news, referring to textual contents, entity occurrences, and temporal ordering. These similarities are captured in a multi-view attributed graph. To distill canonicalized events, EVIN coarsens the graph by iterative merging based on a judiciously designed loss function. To infer semantic classes of events, EVIN uses statistical language models. EVIN provides a GUI that allows users to query the constructed knowledge base of events, and to explore it in a visual manner.

References

[1]

M. K. Agarwal, et al. Real Time Discovery of Dense Clusters in Highly Dynamic Graphs: Identifying Real World Events in Highly Dynamic Environments. PVLDB, 2012.

Digital Library

Google Scholar

[2]

A. Angel, et al. Dense Subgraph Maintenance under Streaming Edge Weight Updates for Real-time Story Identification. PVLDB, 2012.

Digital Library

Google Scholar

[3]

A. Das Sarma, et al. Dynamic Relationship and Event Discovery. WSDM, 2011.

Digital Library

Google Scholar

[4]

E. Gabrilovich, et al. Overcoming the Brittleness Bottleneck Using Wikipedia: Enhancing Text Categorization with Encyclopedic Knowledge. In AAAI, 2006.

Digital Library

Google Scholar

[5]

X. Hu, et al. Exploiting Wikipedia as External Knowledge for Document Clustering. KDD, 2009.

Digital Library

Google Scholar

[6]

Y. Rui, et al. Evolutionary Timeline Summarization: A Balanced Optimization Framework via Iterative Substitution. In SIGIR, 2011.

Digital Library

Google Scholar

[7]

D. Shahaf, et al. Connecting the Dots Between News Articles. In KDD, 2010.

Digital Library

Google Scholar

[8]

F. M. Suchanek, et al. Yago: A Core of Semantic Knowledge. WWW, 2007.

Digital Library

Google Scholar

[9]

D. Wang, et al. Generating Pictorial Storylines Via Minimum-Weight Connected Dominating Set Approximation in Multi-View Graphs. In AAAI, 2012.

Digital Library

Google Scholar

Cited By

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Yoon SMeng YLee DHan J(2023)SCStory: Self-supervised and Continual Online Story DiscoveryProceedings of the ACM Web Conference 202310.1145/3543507.3583507(1853-1864)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583507
Chen YDing ZZheng QQin YHuang RShah N(2020)A History and Theory of Textual Event Detection and RecognitionIEEE Access10.1109/ACCESS.2020.30349078(201371-201392)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3034907
Poghosyan GDi Caro LCataldi MSchifanella C(2019)Addressing Information Overload through Text Mining across News and Social Media StreamsProceedings of the 5th International Workshop on Social Media World Sensors10.1145/3345645.3351105(1-2)Online publication date: 12-Sep-2019
https://dl.acm.org/doi/10.1145/3345645.3351105
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Index Terms

EVIN: building a knowledge base of events
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation theory
      1. Systems theory
2. Mathematics of computing
  1. Information theory

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Information & Contributors

Information

Published In

WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web

April 2014

1396 pages

ISBN:9781450327459

DOI:10.1145/2567948

General Chair:
Chin-Wan Chung
Korea Advanced Institute of Science and Technology, Korea
,
Program Chairs:
Andrei Broder
Google Inc., USA
,
Kyuseok Shim
Seoul National University, Korea
,
Torsten Suel
New York University, USA

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 April 2014

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Demonstration

Conference

WWW '14

Sponsor:

IW3C2

WWW '14: 23rd International World Wide Web Conference

April 7 - 11, 2014

Seoul, Korea

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Citations

Cited By

View all

Yoon SMeng YLee DHan J(2023)SCStory: Self-supervised and Continual Online Story DiscoveryProceedings of the ACM Web Conference 202310.1145/3543507.3583507(1853-1864)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583507
Chen YDing ZZheng QQin YHuang RShah N(2020)A History and Theory of Textual Event Detection and RecognitionIEEE Access10.1109/ACCESS.2020.30349078(201371-201392)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3034907
Poghosyan GDi Caro LCataldi MSchifanella C(2019)Addressing Information Overload through Text Mining across News and Social Media StreamsProceedings of the 5th International Workshop on Social Media World Sensors10.1145/3345645.3351105(1-2)Online publication date: 12-Sep-2019
https://dl.acm.org/doi/10.1145/3345645.3351105
Gupta SPatel D(2019)$$\hbox {NE}^2$$NE2Knowledge and Information Systems10.1007/s10115-018-1208-859:2(311-335)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1007/s10115-018-1208-8
Setty V(2018)Distributed and Dynamic Clustering For News EventsProceedings of the 12th ACM International Conference on Distributed and Event-based Systems10.1145/3210284.3219774(254-257)Online publication date: 25-Jun-2018
https://dl.acm.org/doi/10.1145/3210284.3219774
Miani RHruschka Junior E(2017)Specific temporal association rules and temporal correlations to enlarge and detect inconsistencies in a large growing knowledge base2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)10.1109/FSKD.2017.8392999(1565-1574)Online publication date: Jul-2017
https://doi.org/10.1109/FSKD.2017.8392999
Miani RHruschka E(2017)Correcting Inconsistencies through Association Rules in Temporal Large Growing Knowledge Bases2017 Brazilian Conference on Intelligent Systems (BRACIS)10.1109/BRACIS.2017.56(1-6)Online publication date: Oct-2017
https://doi.org/10.1109/BRACIS.2017.56
Huang WWang TChen WWang Y(2017)Category-Level Transfer Learning from Knowledge Base to Microblog Stream for Accurate Event DetectionDatabase Systems for Advanced Applications10.1007/978-3-319-55753-3_4(50-67)Online publication date: 22-Mar-2017
https://doi.org/10.1007/978-3-319-55753-3_4
Ceroni AGadiraju UMatschke JWingert SFisichella MPerego RSebastiani FAslam JRuthven IZobel J(2016)Where the Event LiesProceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval10.1145/2911451.2911452(1157-1160)Online publication date: 7-Jul-2016
https://dl.acm.org/doi/10.1145/2911451.2911452
Poghosyan GQureshi MIfrim G(2016)Topy: Real-Time Story Tracking via Social TagsMachine Learning and Knowledge Discovery in Databases10.1007/978-3-319-46131-1_10(45-49)Online publication date: 3-Sep-2016
https://doi.org/10.1007/978-3-319-46131-1_10
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