Data-Driven Dialogue for Interactive Question Answering Export

@incollection{citeulike:3182492, abstract = {In this paper, a light framework for dialogue based interactive question answering is presented. The resulting architecture is called REQUIRE (Robust Empirical QUestion answering for Intelligent Retrieval), and represents a flexible and adaptive platform for domain specific dialogue. REQUIRE characterizes as a domain-driven dialogue system, whose aim is to support the specific tasks evoked by interactive question answering scenarios. Among its benefits it should be mentioned its modularity and portability across different domains, its robustness through adaptive models of speech act recognition and planning and its adherence of knowledge representation standard. The framework will be exemplified through its application within a sexual health information service tailored to young people.}, author = {Basili, Roberto and De Cao, Diego and Giannone, Cristina and Marocco, Paolo}, citeulike-article-id = {3182492}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-540-74782-6_29}, doi = {10.1007/978-3-540-74782-6_29}, journal = {AI*IA 2007: Artificial Intelligence and Human-Oriented Computing}, keywords = {chat, chatbot, dialogue, qa, questionanswering}, pages = {326--338}, posted-at = {2008-09-02 17:55:39}, priority = {2}, title = {Data-Driven Dialogue for Interactive Question Answering}, url = {http://dx.doi.org/10.1007/978-3-540-74782-6_29}, year = {2007} }

TY - CHAP ID - citeulike:3182492 L3 - citeulike-article-id:3182492 N2 - In this paper, a light framework for dialogue based interactive question answering is presented. The resulting architecture is called REQUIRE (Robust Empirical QUestion answering for Intelligent Retrieval), and represents a flexible and adaptive platform for domain specific dialogue. REQUIRE characterizes as a domain-driven dialogue system, whose aim is to support the specific tasks evoked by interactive question answering scenarios. Among its benefits it should be mentioned its modularity and portability across different domains, its robustness through adaptive models of speech act recognition and planning and its adherence of knowledge representation standard. The framework will be exemplified through its application within a sexual health information service tailored to young people. JF - AI*IA 2007: Artificial Intelligence and Human-Oriented Computing EP - 338 TI - Data-Driven Dialogue for Interactive Question Answering SP - 326 KW - chat KW - chatbot KW - dialogue KW - qa KW - questionanswering AU - Basili, Roberto AU - De Cao, Diego AU - Giannone, Cristina AU - Marocco, Paolo PY - 2007/// UR - http://dx.doi.org/10.1007/978-3-540-74782-6_29 ER -