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In this paper, we study how the performance and usability of web dialogue systems could be enhanced by using an appropriate representation of the different types of knowledge involved in communication: general dialogue mechanisms, specific domainrestricted linguistic and conceptual knowledge and information on how well the communication process is doing. We describe the experiments carried out to analyze how to improve this knowledge representation in the web dialogue system we developed. the system to the user’s expertise and application complexity we have distinguished two types of messages: directed and open. Directed system's messages are explicit about the information the system needs from the user at each state of the communication. Open system's messages suggest the user to introduce the information needed, but not as strongly. Although different types of messages could be used, the initiative (or control) of the dialogue is always mixed because the user can decide to select a new task at any state of the communication and the system will always guide the user to introduce the needed information. In order to improve the adaptability of the DS several systems (,) dynamically adapt the dialogue strategy. In our DS we have incorporated an independent module that uses data on how well the communication is doing to determine the type of message and the confirmation policy. Following the methodology proposed in  we analyzed a corpus of dialogues to obtain the data that gives information about the most appropiate system stategy and the amount of evidence each data gives. The dialogue cues used by the adaptive module to determine the system’s respond are related to the system’s errors as well as to the content of the user’s intervention (asking for help, giving new relevant data and giving not expected data).
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