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        <title>A Spreading Activation Framework for Tracking Conceptual Complexity of Texts</title>
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        <namePart type="given">Ioana</namePart>
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        <namePart type="given">Sanja</namePart>
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            <namePart type="given">Anna</namePart>
            <namePart type="family">Korhonen</namePart>
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            <namePart type="given">David</namePart>
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    <abstract>We propose an unsupervised approach for assessing conceptual complexity of texts, based on spreading activation. Using DBpedia knowledge graph as a proxy to long-term memory, mentioned concepts become activated and trigger further activation as the text is sequentially traversed. Drawing inspiration from psycholinguistic theories of reading comprehension, we model memory processes such as semantic priming, sentence wrap-up, and forgetting. We show that our models capture various aspects of conceptual text complexity and significantly outperform current state of the art.</abstract>
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    <identifier type="doi">10.18653/v1/P19-1377</identifier>
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%0 Conference Proceedings
%T A Spreading Activation Framework for Tracking Conceptual Complexity of Texts
%A Hulpu\textcommabelows, Ioana
%A Štajner, Sanja
%A Stuckenschmidt, Heiner
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F hulpus-etal-2019-spreading
%X We propose an unsupervised approach for assessing conceptual complexity of texts, based on spreading activation. Using DBpedia knowledge graph as a proxy to long-term memory, mentioned concepts become activated and trigger further activation as the text is sequentially traversed. Drawing inspiration from psycholinguistic theories of reading comprehension, we model memory processes such as semantic priming, sentence wrap-up, and forgetting. We show that our models capture various aspects of conceptual text complexity and significantly outperform current state of the art.
%R 10.18653/v1/P19-1377
%U https://aclanthology.org/P19-1377
%U https://doi.org/10.18653/v1/P19-1377
%P 3878-3887

Markdown (Informal)

[A Spreading Activation Framework for Tracking Conceptual Complexity of Texts](https://aclanthology.org/P19-1377) (Hulpuș et al., ACL 2019)

• A Spreading Activation Framework for Tracking Conceptual Complexity of Texts (Hulpuș et al., ACL 2019)

ACL

• Ioana Hulpuș, Sanja Štajner, and Heiner Stuckenschmidt. 2019. A Spreading Activation Framework for Tracking Conceptual Complexity of Texts. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3878–3887, Florence, Italy. Association for Computational Linguistics.