517 research outputs found
Interfacing a Conversational Agent with Contextual Knowledge Drawn from Wikipedia
No full textBreuing A. Interfacing a Conversational Agent with Contextual Knowledge Drawn from Wikipedia. In: Proceedings of the KogWis 2010. Potsdam: Universitätsverlag Potsdam; 2010: 58-59
Künstliches Themenbewusstsein in natürlichen Dialogen
No full textBreuing A. Künstliches Themenbewusstsein in natürlichen Dialogen. Bielefeld: Bielefeld University; 2012
Improving Human-Agent Conversations by Accessing Contextual Knowledge from Wikipedia
No full textBreuing A. Improving Human-Agent Conversations by Accessing Contextual Knowledge from Wikipedia. In: Proceedings of the 3rd WI-IAT Doctoral Workshop, in conj. with the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. IEEE; 2010: 428-431
Equipping a conversational agent with access to Wikipedia knowledge
No full textBreuing A, Wachsmuth I. Equipping a conversational agent with access to Wikipedia knowledge. In: Proceedings of the KogWis 2010. Potsdam: Universitätsverlag Potsdam; 2010: 89-89
Talking topically to the artificial agent Max
No full textBreuing A, Waltinger U, Wachsmuth I. Talking topically to the artificial agent Max. In: Postersession at the Interdisciplinary College. Sankt Augustin, Germany; 2011: 488
Digital fruits for lunch: Feeding embodied conversational agents with Wikipedia knowledge
No full textWaltinger U, Breuing A, Wachsmuth I. Digital fruits for lunch: Feeding embodied conversational agents with Wikipedia knowledge. In: Postersession at the Interdisciplinary College. Sankt Augstin: Interdisciplinary College; 2011: 524
Internet-based Communication
No full textWaltinger U, Breuing A. Internet-based Communication. In: Mehler A, Romary L, Gibbon D, eds. Handbook of Applied Linguistics. Vol Technical Communication. Berlin/New York: Mouton de Gruyter; Submitted
Harvesting Wikipedia knowledge to identify topics in ongoing natural language dialogs
No full textBreuing A, Waltinger U, Wachsmuth I. Harvesting Wikipedia knowledge to identify topics in ongoing natural language dialogs. In: Proceedings of the 2011 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2011). IEEE; 2011: 445-450.This paper introduces a model harvesting the crowd-sourced encyclopedic knowledge provided by Wikipedia to improve the conversational abilities of an artificial agent. More precisely, we present a model for automatic topic identification in ongoing natural language dialogs. On the basis of a graph-based representation of the Wikipedia category system, our model implements six tasks essential for detecting the topical overlap of coherent dialog contributions. Thereby the identification process operates online to handle dialog streams of constantly changing topical threads in real-time. The realization of the model and its application to our conversational agent aims to improve human-agent conversations by transferring human-like topic awareness to the artificial interlocutor
Talking topically to artificial dialog partners: Emulating humanlike topic awareness in a virtual agent
No full textBreuing A, Wachsmuth I. Talking topically to artificial dialog partners: Emulating humanlike topic awareness in a virtual agent. In: Filipe J, Fred A, eds. Agents and Artificial Intelligence: 4th International Conference, ICAART 2012, Vilamoura, Portugal, February 6-8, 2012. Revised Selected Papers. Communications in Computer and Information Science. Vol 358. Berlin: Springer; 2013: 392-406.During dialog, humans are able to track ongoing topics, to detect topical shifts, to refer to topics via labels, and to decide on the appropriateness of potential dialog topics. As a result, they interactionally produce coherent sequences of spoken utterances assigning a thematic structure to the whole conversation. Accordingly, an artificial agent that is intended to engage in natural and sophisticated human-agent dialogs should be endowed with similar conversational abilities. This paper presents how to enable topically coherent conversations between humans and interactive systems by emulating humanlike topic awareness in the virtual agent Max. Therefore, we firstly realized automatic topic detection and tracking on the basis of contextual knowledge provided by Wikipedia and secondly adapted the agent’s conversational behavior by means of the gained topic information. As a result, we contribute to improve human-agent dialogs by enabling topical talk between human and artificial interlocutors. This paper is a revised and extended version of A. Breuing and I. Wachsmuth. Let’s talk topically with artificial agents! providing agents with humanlike topic awareness in everyday dialog situations. In Proceedings of the 4th International Conference on Agents and Artificial Intelligence (ICAART), pages 62–71, 2012
Let's talk topically with artificial agents! Providing agents with humanlike topic awareness in everyday dialog situations
No full textBreuing A, Wachsmuth I. Let's talk topically with artificial agents! Providing agents with humanlike topic awareness in everyday dialog situations. In: Proceedings of the 4th International Conference on Agents and Artificial Intelligence (ICAART). Vol 2. Portugal: SciTePress; 2012: 62-71.Spoken interactions between humans are characterized by coherent sequences of utterances assigning a thematical structure to the whole conversation. Such coherence and the success of a meaningful and flexible dialog are based on the cognitive ability to be aware of the ongoing conversational topic. This paper presents how to enable such topically coherent conversations between humans and interactive systems by emulating humanlike topic awareness in artificial agents. Therefore, we firstly automated human topic awareness on the basis of preprocessed Wikipedia knowledge and secondly transferred such computer-based awareness to a virtual agent. As a result, we contribute to improve human-agent dialogs by enabling topical talk between human and artificial conversation partners
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