Using a Dialogue Manager to Improve Semantic Web Search

Related Work

Cooperative QA systems are automatic systems of question and answer that automatically collaborate with the users, in order to obtain the information and clarification needed to provide the correct answer. These systems provide the user with additional information, intermediate answers, qualified answers and/or alternative questions. An approach for processing cooperatives answers over databases is presented in (Minker, 1998). In (McGuinness, 2004) the author presents a set of techniques that promote the enhancement, its potential and impact on QA systems. Farah Benamara presents several works in this area: in (Benamara, 2004b), presents a logic-based model for accurate generation of intentional answers using a Cooperative QA system; in (Benamara, 2004a), presents a proposal for construction of a Logic-Based QA system, WEBCOOP, that integrates knowledge representation and advanced strategies of reasoning to generate cooperative answers to web queries. More recently, in (Bakhtyar, Dang, Inoue, & Wiese, 2014), the authors present an implementation of conceptual inductive learning operators in a prototype system for cooperative query answering, which can also be used as a usual concept learning mechanism for concepts described in first-order predicate logic.