User modeling

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

Adaptive multi-tier authentication system

Abstract: An adaptive multi-tier authentication system provides secondary tiers of authentication which are used only when the user attempts a connection from a new environment. The invention accepts user input such as login attempts and responses to the system's questions. User login information such as IP address, originating phone number, or cookies on the user's machine are obtained for evaluation. User/usage profiles are kept for each user and the user login information is compared to the information from the user/usage profile for the specific user which contains all of the user information that the user used to establish the account and also the usage profile detailing the user's access patterns. The trust level of the current user login location is calculated and the invention determines if any additional questions to the user are required. If the trust level is high, then the user is granted access to the system. If the trust level is not high enough, then questions are sent to the user and the user's answers are evaluated and access is granted or denied based on the trust level and answers. The user's profile is updated to reflect the access attempt.

Natural user input for driving interactive stories

Abstract: A system and method are disclosed for combining interactive gaming aspects into a linear story. A user may interact with the linear story via a NUI system to alter the story and the images that are presented to the user. In an example, a user may alter the story by performing a predefined exploration gesture. This gesture brings the user into the 3-D world of the displayed image. In particular, the image displayed on the screen changes to create the impression that a user is stepping into the 3-D virtual world to allow a user to examine virtual objects from different perspectives or to peer around virtual objects.

Dynamic detection of novice vs. skilled use without a task model

Abstract: If applications were able to detect a user's expertise, then software could automatically adapt to better match exper-tise. Detecting expertise is difficult because a user's skill changes as the user interacts with an application and differs across applications. This means that expertise must be sensed dynamically, continuously, and unobtrusively so as not to burden the user. We present an approach to this prob-lem that can operate without a task model based on low-level mouse and menu data which can typically be sensed across applications at the operating systems level. We have implemented and trained a classifier that can detect "nov-ice" or "skilled" use of an image editing program, the GNU Image Manipulation Program (GIMP), at 91% accuracy, and tested it against real use. In particular, we developed and tested a prototype application that gives the user dy-namic application information that differs depending on her performance.

System and method of selecting a relevant user for introduction to a user in an online environment

Abstract: Systems and methods of selecting a relevant user for introduction to a user in an online environment are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of receiving a request to identify the relevant user to be introduced to the participating user in the social network, identifying a set of social history records that occurred among the multiple users in the social network, selecting, from the multiple users, the relevant user to be introduced to the participating user using the set of social history records. The relevant user that is selected is not a social connection of the participating user in the social network. One embodiment includes, determining whether the participating user is interested in meeting the relevant user in the social network based on an indication made by the participating user via interaction with the user device.

Personalized Conversational Case-Based Recommendation

Abstract: In this paper, we describe the Adaptive Place Advisor, a user adaptive, conversational recommendation system designed to help users decide on a destination, specifically a restaurant. We view the selection of destinations as an interactive, conversational process, with the advisory system inquiring about desired item characteristics and the human responding. The user model, which contains preferences regarding items, attributes, values, value combinations, and diversification, is also acquired during the conversation. The system enhances the user's requirements with the user model and retrieves suitable items from a case-base. If the number of items found by the system is unsuitable (too high, too low) the next attribute to be constrained or relaxed is selected based on the information gain associated with the attributes. We also describe the current status of the system and future work.