@prefix foaf: . @prefix ns1: . @prefix ns2: . ns1:svitlana-vakulenko foaf:made ns2:iswc-2018-research-104 . ns1:axel-polleres foaf:made ns2:iswc-2018-research-104 . ns1:vadim-savenkov foaf:made ns2:iswc-2018-research-104 . ns1:maarten-de-rijke foaf:made ns2:iswc-2018-research-104 . ns1:michael-cochez foaf:made ns2:iswc-2018-research-104 . @prefix ns3: . @prefix ns4: . ns4:proceedings ns3:hasPart ns2:iswc-2018-research-104 . @prefix rdf: . ns2:iswc-2018-research-104 rdf:type ns3:InProceedings . @prefix rdfs: . ns2:iswc-2018-research-104 rdfs:label "Measuring Semantic Coherence of a Conversation" . @prefix dc: . ns2:iswc-2018-research-104 dc:creator ns1:michael-cochez , ns1:vadim-savenkov , ns1:axel-polleres , ns1:maarten-de-rijke , ns1:svitlana-vakulenko ; ns3:abstract "Conversational systems have become increasingly popular as a way for humans to interact with computers. To be able to provide intelligent responses, conversational systems must correctly model the structure and semantics of a conversation. In this paper, we introduce the task of measuring semantic (in)coherence in a conversation with respect to the background knowledge, which relies on identification of semantic relations between concepts introduced during a conversation. We propose and evaluate graph-based and machine learning approaches for measuring semantic coherence using knowledge graphs, their vector space embeddings and word embedding models, as sources of background knowledge. We demonstrate in our evaluation results how these approaches are able to uncover different coherence patterns in conversations on the Ubuntu Dialogue Corpus." . @prefix ns8: . ns2:iswc-2018-research-104 ns3:hasAuthorList ns8:iswc-2018-research-104 ; ns3:isPartOf ns4:proceedings . @prefix xsd: . ns2:iswc-2018-research-104 ns3:keyword "discourse analysis"^^xsd:string , "natural language understanding"^^xsd:string , "semantic coherence"^^xsd:string , "dialogue"^^xsd:string ; ns3:title "Measuring Semantic Coherence of a Conversation" . @prefix ns10: . ns10:iswc2018-author-axel-polleres-iswc-2018-research-104 ns3:withDocument ns2:iswc-2018-research-104 . ns10:iswc2018-author-maarten-de-rijke-iswc-2018-research-104 ns3:withDocument ns2:iswc-2018-research-104 . ns10:iswc2018-author-michael-cochez-iswc-2018-research-104 ns3:withDocument ns2:iswc-2018-research-104 . ns10:iswc2018-author-svitlana-vakulenko-iswc-2018-research-104 ns3:withDocument ns2:iswc-2018-research-104 . ns10:iswc2018-author-vadim-savenkov-iswc-2018-research-104 ns3:withDocument ns2:iswc-2018-research-104 .