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          <titl xml:lang="en">DDI study level documentation for study 10.7802/1372 Sowiport user queries sample (SQS)</titl>
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        <titl xml:lang="en">Sowiport user queries sample (SQS)</titl>
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        <IDNo xml:lang="en" agency="GESIS">10.7802/1372</IDNo><IDNo xml:lang="de" agency="GESIS">10.7802/1372</IDNo><IDNo xml:lang="en" agency="DOI">10.7802/1372</IDNo><IDNo xml:lang="de" agency="DOI">10.7802/1372</IDNo>
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        <AuthEnty affiliation="GESIS - Leibniz Institute for the Social Sciences" xml:lang="en">Mayr, Philipp
        </AuthEnty><AuthEnty affiliation="GESIS - Leibniz Institute for the Social Sciences" xml:lang="de">Mayr, Philipp
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      <abstract xml:lang="en">This data set contains a random sample of 1,800 user queries taken from the transaction log of the academic search engine sowiport (www.sowiport.de). The queries (mainly German query terms) were extracted from a larger set of randomly chosen user sessions which have been recorded in sowiport between September 1st 2014 and March 1st 2015. To reduce noise in the data set, we selected sessions in which at least two different searches were conducted and at least one document has been clicked on. In addition, we excluded all searches for numbers (mostly ISSN numbers). The selected queries were sorted randomly and manually assessed by a domain expert. The randomness was introduced to reduce potential biases in the assessment. When assessing multiple queries from one session, the previous queries might influence the decision for following queries as they are then evaluated within a context. The 1,800 user queries were categorized into the 29 facets of the subject categories used in the Thesaurus Social Sciences (TheSoz, see http://lod.gesis.org/thesoz/en.html and http://sowiport.gesis.org/thesaurus?view=systematic&amp;lang=en). It was allowed to apply multiple facets, as some queries cover multiple topics. &lt;br&gt; This work was funded by Deutsche Forschungsgemeinschaft (DFG), grant no. MA 3964/5-1;the AMUR project at GESIS.</abstract><abstract xml:lang="de">This data set contains a random sample of 1,800 user queries taken from the transaction log of the academic search engine sowiport (www.sowiport.de). The queries (mainly German query terms) were extracted from a larger set of randomly chosen user sessions which have been recorded in sowiport between September 1st 2014 and March 1st 2015. To reduce noise in the data set, we selected sessions in which at least two different searches were conducted and at least one document has been clicked on. In addition, we excluded all searches for numbers (mostly ISSN numbers). The selected queries were sorted randomly and manually assessed by a domain expert. The randomness was introduced to reduce potential biases in the assessment. When assessing multiple queries from one session, the previous queries might influence the decision for following queries as they are then evaluated within a context. The 1,800 user queries were categorized into the 29 facets of the subject categories used in the Thesaurus Social Sciences (TheSoz, see http://lod.gesis.org/thesoz/en.html and http://sowiport.gesis.org/thesaurus?view=systematic&amp;lang=en). It was allowed to apply multiple facets, as some queries cover multiple topics. &lt;br&gt; This work was funded by Deutsche Forschungsgemeinschaft (DFG), grant no. MA 3964/5-1;the AMUR project at GESIS.</abstract>
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CC BY-NC-ND 4.0: Namensnennung - Nicht kommerziell – Keine Bearbeitung  (http://creativecommons.org/licenses/by-nc-nd/4.0/deed.de)</restrctn><restrctn xml:lang="de">Freier Zugang (ohne Registrierung) - Die Forschungsdaten können von jedem direkt heruntergeladen werden.
CC BY-NC-ND 4.0: Namensnennung - Nicht kommerziell – Keine Bearbeitung  (http://creativecommons.org/licenses/by-nc-nd/4.0/deed.de)</restrctn>
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