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    <titleInfo>
        <title>Dish Classification using Knowledge based Dietary Conflict Detection</title>
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    <name type="personal">
        <namePart type="given">Nadia</namePart>
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            <title>Proceedings of the Student Research Workshop Associated with RANLP 2017</title>
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        <name type="personal">
            <namePart type="given">Venelin</namePart>
            <namePart type="family">Kovatchev</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Irina</namePart>
            <namePart type="family">Temnikova</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Pepa</namePart>
            <namePart type="family">Gencheva</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Yasen</namePart>
            <namePart type="family">Kiprov</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Ivelina</namePart>
            <namePart type="family">Nikolova</namePart>
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            <publisher>INCOMA Ltd.</publisher>
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    <abstract>The present paper considers the problem of dietary conflict detection from dish titles. The proposed method explores the semantics associated with the dish title in order to discover a certain or possible incompatibility of a particular dish with a particular diet. Dish titles are parts of the elusive and metaphoric gastronomy language, their processing can be viewed as a combination of short text and domain-specific texts analysis. We build our algorithm on the basis of a common knowledge lexical semantic network and show how such network can be used for domain specific short text processing.</abstract>
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    <identifier type="doi">10.26615/issn.1314-9156.2017_001</identifier>
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%0 Conference Proceedings
%T Dish Classification using Knowledge based Dietary Conflict Detection
%A Clairet, Nadia
%Y Kovatchev, Venelin
%Y Temnikova, Irina
%Y Gencheva, Pepa
%Y Kiprov, Yasen
%Y Nikolova, Ivelina
%S Proceedings of the Student Research Workshop Associated with RANLP 2017
%D 2017
%8 September
%I INCOMA Ltd.
%C Varna
%F clairet-2017-dish
%X The present paper considers the problem of dietary conflict detection from dish titles. The proposed method explores the semantics associated with the dish title in order to discover a certain or possible incompatibility of a particular dish with a particular diet. Dish titles are parts of the elusive and metaphoric gastronomy language, their processing can be viewed as a combination of short text and domain-specific texts analysis. We build our algorithm on the basis of a common knowledge lexical semantic network and show how such network can be used for domain specific short text processing.
%R 10.26615/issn.1314-9156.2017_001
%U https://doi.org/10.26615/issn.1314-9156.2017_001
%P 1-9

Markdown (Informal)

[Dish Classification using Knowledge based Dietary Conflict Detection](https://doi.org/10.26615/issn.1314-9156.2017_001) (Clairet, RANLP 2017)

• Dish Classification using Knowledge based Dietary Conflict Detection (Clairet, RANLP 2017)

ACL

• Nadia Clairet. 2017. Dish Classification using Knowledge based Dietary Conflict Detection. In Proceedings of the Student Research Workshop Associated with RANLP 2017, pages 1–9, Varna. INCOMA Ltd..