User modeling

About: User modeling is a research topic. Over the lifetime, 10701 publications have been published within this topic receiving 278012 citations.

System and method for accessing data via Internet, wireless PDA, smartphone, text to voice and voice to text

Abstract: An intermediary system and method are disclosed for providing users access to enterprise data via the Internet, Wireless PDA, VoIP Phone, Wireless Phone, and GSM/EDGE SmartPhone, and other communication devices. The intermediary system allows users to access enterprise data based on the user's role in the enterprise, the user's assigned privileges, or the user's object permissions. The intermediary system tailors the enterprise data for the user based on the type of communication device of the user, the point in time the user communicates with the system, or the location in a network where the user is communicating with the system. Depending on the above criteria, the user is given a “view” of the enterprise data that relates more directly to the user's current needs, duties, and tasks.

Personalized information retrieval based on context and ontological knowledge

Abstract: Context modeling has long been acknowledged as a key aspect in a wide variety of problem domains. In this paper we focus on the combination of contextualization and personalization methods to improve the performance of personalized information retrieval. The key aspects in our proposed approach are (1) the explicit distinction between historic user context and live user context, (2) the use of ontology-driven representations of the domain of discourse, as a common, enriched representational ground for content meaning, user interests, and contextual conditions, enabling the definition of effective means to relate the three of them, and (3) the introduction of fuzzy representations as an instrument to properly handle the uncertainty and imprecision involved in the automatic interpretation of meanings, user attention, and user wishes. Based on a formal grounding at the representational level, we propose methods for the automatic extraction of persistent semantic user preferences, and live, ad-hoc user interests, which are combined in order to improve the accuracy and reliability of personalization for retrieval.

Affective recommender systems: The role of emotions in recommender systems

Abstract: Recommender systems have traditionally relied on data-centric descriptors for content and user modeling. In recent years we have witnessed an increasing number of attempts to use emotions in different ways to improve the quality of recommender systems. In this paper we introduce a unifying framework that positions the research work, that has been done so far in a scattered manner, in a three stage model. We provide examples of research that cover various aspects of the detection of emotions and the inclusion of emotions into recommender systems.

A statistical model for user preference

Abstract: Modeling user preference is one of the challenging issues in intelligent information systems. Extensive research has been performed to automatically analyze user preference and to utilize it. One problem still remains: The representation of preference, usually given by measure of vector similarity or probability, does not always correspond to common sense of preference. This problem gets worse in the case of negative preference. To overcome this problem, this paper presents a preference model using mutual information in a statistical framework. This paper also presents a method that combines information of joint features and alleviates problems arising from sparse data. Experimental results, compared with the previous recommendation models, show that the proposed model has the highest accuracy in recommendation tests.

KN-AHS: an adaptive hypertext client of the user modeling system BGP-MS

Abstract: This paper describes the automatic adaptation of hypertext to the user’s presumed domain knowledge in the KN-AHS system, and the support that the user modeling shell system BGP-MS can provide for this adaptation. First, basic hypertext concepts will be introduced and reasons given for why hypertext should adapt to the current user (especially to his/her state of knowledge). A brief overview of those representation and inference components of BGP-MS that are used by KN-AHS will then be provided, followed by a description of its adaptive user interface. The interaction between the adaptive hypertext system and the user modeling system will be investigated in detail based on a possible dialog with a user. Finally, the inter-process communication between KN-AHS and BGP-MS will be described and related work discussed. The aim of this work was to demonstrate the feasibility of user modeling with BGP-MS in a “normal” hardware and software environment that is frequently found in the workplace.