Towards a Natural Language Driven Automated Help Desk Melanie Knapp1 and Jens Woch2 1
Institute of Computer Science III University of Bonn, Germany 2 Department of Computer Science University of Koblenz, Germany
Abstract. In this paper, we present the linguistic components required for a natural language driven automated help desk. This work is significant for two reasons: First, the combination of neural networks and supertagging represents a novel and very robust way to classify non-trivial user utterances. Second, we show a novel way of integrating known linguistic techniques for the analysis of user input, knowledge processing, and generation of system responses, resulting in a natural language interface both for input and output. Our approach separates domain specific, language specific and discourse specific knowledge.
1 Introduction The rapid development of technologies associated with the World Wide Web offers the possibility of a new, relatively inexpensive and effective standard user interface to help desks and appears to encourage more automation in help desk service. Typically, a help desk is defined as centralized help to users within an enterprise. Independent from the actual domain, help desks have to deal with two main problems: (1) efficient use of the know-how of an employee and (2) cost-efficient handling of many support requests. In this light, we present a natural language driven approach for modeling an automated help desk. This objective is motivated by the evaluation of support requests which showed that for 80 percent of all requests no specialized knowledge is needed. Hence, a solution database is sufficient for routine requests. Under this condition, our research concentrates on a computer-based so-called first support level. Modeling a first support level requires the definition of all processing steps in a generic help desk system. We define a system structure with three main components. Within this design we do not distinguish among various input capabilities (e.g. telephone call, email, chat, fax or letter) and their appropriate analysis techniques. The first step in finding solutions is to analyze the textual input (independent of the extraction method) and to reduce the support request to a specific problem class. The second step is to request missing task parameters from the user. If the user’s initial input is explicit, this step may be skipped. The third step in a generic help desk system is the verification of the specified solution. If the user is not satisfied with the solution, more task parameters for finding the solution must be extracted. In cases where no more task parameters This work partly is funded by the German Research Foundation.
can be asked, the user request has to be delegated to a higher support level together with the already existing query information. Our claim is that all three steps in the aforementioned generic system can be processed automatically. The automation should be based on a linguistically motivated solution, because empirical evaluations demonstrate that adaption to the user’s dialogue preference leads to significantly higher user satisfaction and task success (cf. [Litman et al., 1998]). Wizard-of-Oz experiments by Boje (cf. [Boje et al., 1999]) also point out that users of automatic dialogue systems would like to take the initiative in many dialogues instead of answering a long list of tiny little questions. For modeling user-initiative dialogue systems, one important objective is to avoid leaving a user without a clear understanding of his/her options at a given point in the dialogue. Hence, for the design of the algorithm we define the following criteria: (1) the formulation of the user request should not be restricted, (2) no unnatural breaks between the user input and the result of the computer (especially for telephone calls, real time response must be guaranteed) and (3) no further inquiries into already explicitly or implicitly mentioned facts. A first approach of modeling user-initiative i