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dc.contributor.author노형종en_US
dc.date.accessioned2014-12-01T11:48:54Z-
dc.date.available2014-12-01T11:48:54Z-
dc.date.issued2013en_US
dc.identifier.otherOAK-2014-01483en_US
dc.identifier.urihttp://postech.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000001625421en_US
dc.identifier.urihttp://oasis.postech.ac.kr/handle/2014.oak/1985-
dc.descriptionDoctoren_US
dc.description.abstractThis paper presents a new hybrid dialog management framework that integrates a statistical ranking algorithm into an example-based dialog management approach for chat-like dialogs. The proposed model uses ranking features that consider various aspects of dialogs, including the relative importance of speech acts, dialog history sequences, and the causal relationships among speech acts and slot-filling states. The ranking algorithm enables one to aggregate these feature scores systematically and to generate diverse system responses. Additionally, the model provides detailed feedback by analyzing the causal relationships among speech acts and predicting the user’s possible intentions associated with a given dialog states. Simulated experimental results demonstrate that our approach is effective for task-oriented dialogs and chat-like dialogs. Additionally, a case study using elementary school students implies that the proposed system can be used for language learning purposes in addition to task-oriented services.en_US
dc.languageengen_US
dc.publisher포항공과대학교en_US
dc.rightsBY_NC_NDen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.0/kren_US
dc.titleRanking-based Dialog Management Approaches for Non-task-oriented Conversationsen_US
dc.typeThesisen_US
dc.contributor.college일반대학원 컴퓨터공학과en_US
dc.date.degree2013- 8en_US

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