Towards a Two-Dimensional Framework for User Models

The focus if this paper is user modeling in the context of personalization of information systems. Such a personalization is essential to give users the feeling that the system is easily accessible. The way this adaptive personalization works is very dependent on the adaptation model that is chosen. We introduce a generic two-dimensional classification framework for user modeling systems. This enables us to clarify existing as well as new applications in the area of user modeling. In order to illustrate our framework we evaluate push and pull based user modeling

Acquiring and Using Limited User Models in NLG

It is a truism of NLG that good knowledge of the reader can improve the quality of generated texts, and many NLG systems have been developed that exploit detailed user models when generating texts. Unfortunately, it is very difficult in practice to obtain detailed information about users. In this paper we describe our experiences in acquiring and using limited user models for NLG in four different systems, each of which took a different approach to this issue. One general conclusion is that it is useful if imperfect user models are understandable to users or domain experts, and indeed perhaps can be directly edited by them; this agrees with recent thinking about user models in other applications such as intelligent tutoring systems (Kay, 2001)

Fish or Fowl: A Wizard of Oz Evaluation of Dialogue Strategies in the Restaurant Domain

Recent work on evaluation of spoken dialogue systems suggests that the information presentation phase of complex dialogues is often the primary contributor to dialogue duration. This indicates that better algorithms are needed for the presentation of complex information in speech. Currently however we lack data about the tasks and dialogue strategies on which to base such algorithms. In this paper, we describe a Wizard of Oz tool and a study which applies user models based on multi-attribute decision theory to the problem of generating tailored and concise system responses for a spoken dialogue system. The resulting Wizard corpus will be distributed by the LDC as part of our work on the ISLE project

Implicit Acquisition of User Models in Cooperative Advisory Systems

User modelling systems to date have relied heavily on user models that were hand crafted for use in a particular situation. Recently, attention has focused on the feasibility of general user models, models that can be transferred from one situation to another with little or no modification. Such a general user model could be implemented as a modular component easily integrated into diverse systems. This paper addresses one class of general user models, those general with respect to the underlying domain of the application. In particular, a domain independent user modelling module for cooperative advisory systems is discussed. A major problem in building user models is the difficulty of acquiring information about the user. Traditional approaches have relied heavily on information that is pre-encoded by the system designer. For a user model to be domain independent, acquisition of knowledge will have to be done implicitly, i.e., knowledge about the user must be acquired during his interaction with the system. The research proposed in this paper focuses on domain independent implicit user model acquisition techniques for cooperative advisory systems. These techniques have been formalized as a set of model acquisition rules that will serve as the basis for the implementation of the model acquisition portion of a general user modelling module. The acquisition rules have been developed by studying a large number of conversations between advice-seekers and an expert. The rules presented are capable of supporting most of the modelling requirements of the expert in these conversations. Future work includes implementing these acquisition rules in a general user modelling module to test their effectiveness and domain independence

A generic engine for user model based adaptation

User model based adaptation becomes more and more important in interactive systems. In this paper we first review the di#erent possible adaptation models and discuss the concepts of push, pull and hybrid adaptation. We realize that there is little known explicitly hybrid adaptation. We thus propose a way to add hybrid adaptation (which also provides push and pull adaptation) to interactive systems. Consequently such interactive systems combine the advantages of push and pull adaptation in a domain dependend way

A Personalized System for Conversational Recommendations

Searching for and making decisions about information is becoming increasingly difficult as the amount of information and number of choices increases. Recommendation systems help users find items of interest of a particular type, such as movies or restaurants, but are still somewhat awkward to use. Our solution is to take advantage of the complementary strengths of personalized recommendation systems and dialogue systems, creating personalized aides. We present a system -- the Adaptive Place Advisor -- that treats item selection as an interactive, conversational process, with the program inquiring about item attributes and the user responding. Individual, long-term user preferences are unobtrusively obtained in the course of normal recommendation dialogues and used to direct future conversations with the same user. We present a novel user model that influences both item search and the questions asked during a conversation. We demonstrate the effectiveness of our system in significantly reducing the time and number of interactions required to find a satisfactory item, as compared to a control group of users interacting with a non-adaptive version of the system

The Dual Algorithm

This project was developed out of philosophical concerns rather than systems analysis. Wittgenstein said that the foundations of the language game cannot be part of the language. I reinterpret this comment as dividing mental activity into two algorithms. The foreground includes the language game. The illusive background is more abstract than language. I posit that the foreground includes the language game of Wittgenstein. I also posit that the foreground includes picture or graphic references that are more abstract than language, but not as abstract as the true background. With Wittgenstein the background (foundations) is more action or doing oriented. The foreground of pictures and language is more structure oriented

The Distributed User Modeling Shell System (DUMSS): A Conceptual Framework for Eliciting User Models

With the advances in communication technology, large volumes of information can transfer across continents within a fraction of a second. Nevertheless, computer users still suffer from unpleasant situations when they interact with systems and are required to adapt to systems rather than the other way round. User modeling aims to overcome this problem by enabling computer systems to interact with users according to the users’ models, i.e., goals, knowledge, and preferences of users. Although, user modeling has shown invaluable benefits, methods of capturing user information to build precise and useful user models are still in their early states. This paper proposes a new approach for gathering user information by pooling the information from different systems. This concept, entitled Distributed User Modeling (DUM) is based on a method in which sensors built into each system contribute specific user information to the pooling. Having multiple sources of user information increases the possibility that a system can generate reliable user models. A general model of DUM is presented in this paper. The conceptual framework of the Distributed Fuzzy Object-Oriented User Modeling System (DFOOUMS) that uses DUM as its basis structure is also presented

A Taxonomy of Web Personalization

Web personalization has become an important way to provide individualized user experiences. As a fragmented use of the term “Web personalization” and a lack of a common framework potentially hinder the establishment of a cumulative body of research, we develop a taxonomy of Web personalization. Bringing together research from information systems, computer science, and marketing, we develop a taxonomy focusing on the meta-characteristics user modeling (with the dimensions type of data, acquisition method, and life span of data) and system adaptation (with the dimensions object, volatility, scope, and control of adaptation). We demonstrate an application of our taxonomy by analyzing a sample of articles published in premier information systems journals and present some exemplary use cases to demonstrate how the taxonomy could be applied in practical contexts