Domain Knowledge Model for Embodied Conversation Agent

INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY SCIENCES AND ENGINEERING, 2024

By identifying concept associations during talks and drawing on prior knowledge, ontology-based chatbots preserve context. Even while these agents are able to adjust to their environment, in hostile circumstances they could still display abnormalities. These discrepancies could lead to poor action planning and ineffective adaptation. Therefore, we present a dynamic ontology-based conversational model that selects the best suited answer based on prior experience and knowledge base in order to better action planning and adaptation in hostile scenarios. Since emotions are important in human existence, our method shows the emotional state for different conversational agents instead of only emojis. For this reason, our research will illustrate a conversational bot that functions in a lifelike manner. We employ the ontology Relamodel for ontology, which consists of three parts (C, R,).

2001

Abstract. This paper describes a conversational agent that supports knowledge creation in a community. We propose a conversational agent called virtualized-ego that represents the other self of a community member and can talk on behalf of the member. Knowledge of a virtualized-ego is compiled from everyday e-mails of a real community member. We have developed a system called EgoChat to investigate the ideas of supporting community knowledge creation by using virtualized-egos.

2007

The main aim of this research is to investigate a novel technique for implementing a conversational intelligent agent system on the web. The research will focus on a multilevel natural language query approach. While the present World Wide Web provides a distributed hypermedia interface to the vast amount of information on the Internet, there is a lack of appropriate metadata to that content. Instead of being a giant library as intended, increasing sections of the Web resemble a giant garbage dump. A multilevel natural language query system is described in this paper for the representation of knowledge in specific and open domains. The six-layer conversational agent system includes Spellcheck, Natural Language Understanding and Reasoning, FAQChat, Metadata Index Search, Pattern Matching and Case-Based Reasoning, and Supervised Learning. This technique is demonstrated using extracts from queries on the field of data relating to the Bird Flu H5N1 pandemic crisis.

Information Technology

In this paper, we proposed a new framework to incorporate an intelligent agent software robot into a crisis communication portal (CCNet) in order to send alert news to subscribed users via email and other mobile services such as Short Message Service (SMS), Multimedia Messaging Service (MMS) and General Packet Radio Services (GPRS). The content on the mobile services can be delivered either through mobile phone or Personal Digital Assistance (PDA). This research has shown that with our proposed framework, the embodied conversation agents system can handle questions intelligently with our multilayer architecture. At the same time, the extended framework can take care of delivery content through a more humanoid interface on mobile devices.

2007

The main aim of this research is to investigate a novel technique for implementing a conversational intelligent agent system on the web. The research will focus on a multilevel natural language query approach. While the present World Wide Web provides a distributed hypermedia interface to the vast amount of information on the Internet, there is a lack of appropriate metadata to that content. Instead of being a giant library as intended, increasing sections of the Web resemble a giant garbage dump. A multilevel natural language query system is described in this paper for the representation of knowledge in specific and open domains. The six-layer conversational agent system includes Spellcheck, Natural Language Understanding and Reasoning, FAQChat, Metadata Index Search, Pattern Matching and Case-Based Reasoning, and Supervised Learning. This technique is demonstrated using extracts from queries on the field of data relating to the Bird Flu H5N1 pandemic crisis.

2008

has to be able to carry out general chat conversations and domain specific discussions as well. The structure of the dialogue graph and the attributes of the graph nodes have to support the success of the conversation: user utterance understanding and responding, as well as repairing the “non-understanding ” situations. In the following sections we are briefly depicting the system and describe its dialogue knowledge base focusing on the different user interfaces we developed for its testing and building.

To my parents, Márcio Velmovitsky and Fabiana Elkind Velmovitsky, my sister, Vanessa Elkind Velmovitsky, and my grandparents David Elkind Schwartz and Belinha Saubel Elkind, for the advices and encouragements throughout my life, and for always supporting me in my decisions, no matter what. I would like to thank Professor Lucena for his expert advise and for the opportunity of learning with his experience and knowledge throughout the research process and during my Master degree. To Dr. Marx Leles Viana, for the patience and invaluable support during the making of this work, and to Professor Ruy Luiz Milidiú, for introducing me to the subject of chatbots and encouraging me to pursue further studies in the area. I would like to thanks all my colleagues for their wonderful collaboration. This project would have been imposible without the support of CAPES and PUC-Rio. Thank you.

Communications in Computer and Information Science, 2014

This paper proposes a cognitive architecture of an intelligent agent that can have a dialogue with a human agent on health-related topics. This architecture consists of four main components, namely, the Belief Base, the Dialogue Manager, the Task Manager and the Plan Generator. Each component has sub-components that perform a set of tasks for the purpose to enable the agent to be enrolled in a dialogue. In this paper the particular sub-component of the Dialogue Manager, the Dialogue Strategy has been discussed in detail. A notion of scheme is introduced, which functions as a template with variables that are instantiated each time a state is entered. The agent's dialogue strategy is implemented as a combination of the schemes and the state transitions that the agent makes in response to the human's request. We used a combination of nite-state and agent-based dialogue strategies for dialogue management. This combined dialogue strategy enables a multi-topic dialogue between a human and an agent.

Multimedia Tools and Applications, 2014

In the last few years, the use of ontologies has spread thanks to the irruption of the Semantic Web. They have become a crucial tool in information systems as they explicitly state the meaning of information, making it possible to share it and to achieve higher levels of interoperability. However, being knowledge representation models as they are, other fields can take advantage of their characteristics to extend their capabilities. In particular, in the context of Embodied Conversational Agents, they can be used to provide them with semantic knowledge and, therefore, enhance their intellectual skills. In this paper, we propose an approach to explore the synergies between these technologies. Thus, we have developed a multimodal ECA that exploits the knowledge provided by the Linked Data initiative to help users in their search information tasks. Based on a semantic-guided keyword search, our approach is flexible enough to: 1) deal with different Linked Data repositories and 2) handle different search/knowledge domains in a multilingual way. To illustrate the potential of our approach, we have focused on the case of DBpedia, as it mirrors the information stored in the Wikipedia, providing a semantic entry to it.

Human Computer Interaction is one of the pervasive application areas of computer science to develop with multimodal interaction for information sharings. The conversation agent acts as the major core area for developing interfaces between a system and user with applied AI for proper responses. In this paper, the interactive system plays a vital role in improving knowledge in the domain of health through the intelligent interface between machine and human with text and speech. The primary aim is to enrich the knowledge and help the user in the domain of health using conversation agent to offer immediate response with human companion feel.