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Pure spreading activation is pointless

Authors:

Kilian ThielAuthors Info & Claims

CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management

Pages 1915 - 1918

https://doi.org/10.1145/1645953.1646264

Published: 02 November 2009 Publication History

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Abstract

Almost every application of spreading activation is accompanied by its own set of often heuristic restrictions on the dynamics. We show that in constraint-free scenarios spreading activation would actually yield query-independent results, so that the specific choice of restrictions is not only a pragmatic computational issue, but crucially determines the outcome.

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Cited By

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Schlutter AVogelsang A(2020)Knowledge Extraction from Natural Language Requirements into a Semantic Relation GraphProceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops10.1145/3387940.3392162(373-379)Online publication date: 27-Jun-2020
https://dl.acm.org/doi/10.1145/3387940.3392162
Schlutter AVogelsang A(2020)Trace Link Recovery using Semantic Relation Graphs and Spreading Activation2020 IEEE 28th International Requirements Engineering Conference (RE)10.1109/RE48521.2020.00015(20-31)Online publication date: Aug-2020
https://doi.org/10.1109/RE48521.2020.00015
Torres-Tramon PTimilsina MHayes C(2019)A Diffusion-Based Method for Entity Search2019 IEEE 13th International Conference on Semantic Computing (ICSC)10.1109/ICOSC.2019.8665601(16-23)Online publication date: Jan-2019
https://doi.org/10.1109/ICOSC.2019.8665601
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Index Terms

Pure spreading activation is pointless
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing
    2. Retrieval models and ranking

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Published In

CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management

November 2009

2162 pages

ISBN:9781605585123

DOI:10.1145/1645953

General Chairs:
David Cheung
University of Hong Kong, Hong Kong
,
Il-Yeol Song
Drexel University, USA
,
Program Chairs:
Wesley Chu
UCLA, USA
,
Xiaohua Hu
Drexel University, USA
,
Jimmy Lin
University of Maryland, USA

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: 02 November 2009

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November 2 - 6, 2009

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

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Schlutter AVogelsang A(2020)Knowledge Extraction from Natural Language Requirements into a Semantic Relation GraphProceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops10.1145/3387940.3392162(373-379)Online publication date: 27-Jun-2020
https://dl.acm.org/doi/10.1145/3387940.3392162
Schlutter AVogelsang A(2020)Trace Link Recovery using Semantic Relation Graphs and Spreading Activation2020 IEEE 28th International Requirements Engineering Conference (RE)10.1109/RE48521.2020.00015(20-31)Online publication date: Aug-2020
https://doi.org/10.1109/RE48521.2020.00015
Torres-Tramon PTimilsina MHayes C(2019)A Diffusion-Based Method for Entity Search2019 IEEE 13th International Conference on Semantic Computing (ICSC)10.1109/ICOSC.2019.8665601(16-23)Online publication date: Jan-2019
https://doi.org/10.1109/ICOSC.2019.8665601
Sabetghadam SLupu MRauber A(2017)Role of semantic links in performance of Information Retrieval on graph-based multimodal collections2017 Iranian Conference on Electrical Engineering (ICEE)10.1109/IranianCEE.2017.7985295(1574-1579)Online publication date: May-2017
https://doi.org/10.1109/IranianCEE.2017.7985295
Sun SSong WZomaya AXiang YChoo KShah TWang L(2017)Associative retrieval in spatial big data based on spreading activation with semantic ontologyFuture Generation Computer Systems10.1016/j.future.2016.10.01876:C(499-509)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1016/j.future.2016.10.018
Heitmann BHayes C(2016)SemStim: Exploiting Knowledge Graphs for Cross-Domain Recommendation2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)10.1109/ICDMW.2016.0145(999-1006)Online publication date: Dec-2016
https://doi.org/10.1109/ICDMW.2016.0145
Fähndrich JWeber SAhrndt S(2016)Design and Use of a Semantic Similarity Measure for Interoperability Among AgentsMultiagent System Technologies10.1007/978-3-319-45889-2_4(41-57)Online publication date: 8-Sep-2016
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Fonooni BHellström TJanlert L(2015)Priming as a Means to Reduce Ambiguity in Learning from DemonstrationInternational Journal of Social Robotics10.1007/s12369-015-0292-08:1(5-19)Online publication date: 18-Mar-2015
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Heitmann BDabrowski MHayes CGriffin K(2015)Towards Near Real-Time Social Recommendations for the EnterpriseInnovations in Knowledge Management10.1007/978-3-662-47827-1_9(211-240)Online publication date: 8-Aug-2015
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Shekhar SChakraborti SKhemani D(2015)Spreading Activation Way of Knowledge IntegrationProceedings of the Third International Conference on Mining Intelligence and Knowledge Exploration - Volume 946810.1007/978-3-319-26832-3_1(1-11)Online publication date: 9-Dec-2015
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