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    <titleInfo>
        <title>Anticipating Follow-Up Questions in Exploratory Information Search</title>
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            <title>Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue</title>
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            <namePart type="given">Tatsuya</namePart>
            <namePart type="family">Kawahara</namePart>
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        <name type="personal">
            <namePart type="given">Stefan</namePart>
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            <namePart type="given">David</namePart>
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            <namePart type="given">Kazunori</namePart>
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    <abstract>The paper describes methods for anticipating follow-up questions in exploratory information search. There are two main cases: information stored in knowledge graphs, and information in unstructured texts such as Wikipedia. In the first case, follow-up questions are anticipated by extracting subgraphs relevant to user queries, passing the subgraphs to an LLM to generate responses. In the second case, entities and their relationships are extracted from the texts and added to short-term knowledge graphs relevant to initial queries. Follow-up questions are then anticipated by extracting subgraphs relevant to subsequent queries and passing the subgraphs to the LLM, as in the first case. The short-term graphs in dialogue memory are often sufficient to answer follow-up questions. If they are not, the described steps are repeated as required.</abstract>
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            <start>103</start>
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%0 Conference Proceedings
%T Anticipating Follow-Up Questions in Exploratory Information Search
%A Wilcock, Graham
%Y Kawahara, Tatsuya
%Y Demberg, Vera
%Y Ultes, Stefan
%Y Inoue, Koji
%Y Mehri, Shikib
%Y Howcroft, David
%Y Komatani, Kazunori
%S Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2024
%8 September
%I Association for Computational Linguistics
%C Kyoto, Japan
%F wilcock-2024-anticipating
%X The paper describes methods for anticipating follow-up questions in exploratory information search. There are two main cases: information stored in knowledge graphs, and information in unstructured texts such as Wikipedia. In the first case, follow-up questions are anticipated by extracting subgraphs relevant to user queries, passing the subgraphs to an LLM to generate responses. In the second case, entities and their relationships are extracted from the texts and added to short-term knowledge graphs relevant to initial queries. Follow-up questions are then anticipated by extracting subgraphs relevant to subsequent queries and passing the subgraphs to the LLM, as in the first case. The short-term graphs in dialogue memory are often sufficient to answer follow-up questions. If they are not, the described steps are repeated as required.
%U https://aclanthology.org/2024.sigdial-1.9
%P 103-109

Markdown (Informal)

[Anticipating Follow-Up Questions in Exploratory Information Search](https://aclanthology.org/2024.sigdial-1.9) (Wilcock, SIGDIAL 2024)

• Anticipating Follow-Up Questions in Exploratory Information Search (Wilcock, SIGDIAL 2024)

ACL

• Graham Wilcock. 2024. Anticipating Follow-Up Questions in Exploratory Information Search. In Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 103–109, Kyoto, Japan. Association for Computational Linguistics.