Experiences with an Emotional Sales Agent

With COSIMA B2B we demonstrate a prototype of a complex and visionary e-procurement application. The embodied character agent named COSIMA is able to respect a customer's preferences and deals with him or her via natural speech. She expresses various emotions via mimic, gesture, combined with speech output, and COSIMA is even able to consider the customer's emotions via mimic recognition. As first observations show, this is a very promising approach to improve the bargaining with the customer or the recommendation of products

Personalization of Queries based on User Preferences

Query Personalization is the process of dynamically enhancing a query with related user preferences stored in a user profile with the aim of providing personalized answers. The underlying idea is that different users may find different things relevant to a search due to different preferences. Essential ingredients of query personalization are: (a) a model for representing and storing preferences in user profiles, and (b) algorithms for the generation of personalized answers using stored preferences. Modeling the plethora of preference types is a challenge. In this paper, we present a preference model that combines expressivity and concision. In addition, we provide algorithms for the selection of preferences related to a query and the progressive generation of personalized results, which are ranked based on user interest

Practical Preference Relations for Large Data Sets

User-defined preferences allow personalized ranking of query results. A user provides a declarative specification of his/her preferences, and the system is expected to use that specification to give more prominence to preferred answers. We study constraint formalisms for expressing user preferences as base facts in a partial order. We consider a language that allows comparison and a limited form of arithmetic, and show that the transitive closure computation required to complete the partial order terminates. We consider various ways of composing partial orders from smaller pieces, and provide results on the size of the resulting transitive closures. We introduce the notion of ``covering composition,'' which solves some semantic problems apparent in previous notions of composition. Finally, we show how preference queries within our language can be supported by suitable index structures for efficient evaluation over large data sets. Our results provide guidance about when complex preferences can be efficiently evaluated, and when they cannot

XMatch: A language for satisfaction-based selection of Grid services

Grid systems enable the sharing of a large number of geographically-dispersed resources among different communities of users. They require a mapping functionality for the association of users requests expressed in terms of requirements and preferences to actual resources. This functionality should deal with a potentially high number of similar resources and with the diversity of the perceived satisfactions of users. We propose XMatch, a query language enabling the expression of the user request in terms of the expected satisfaction over XML-based representation of available resources. This language offers a compact way for users to express their preferences for Grid resources and enable the maximization of the global preference

A Context-Aware and Preference-Driven Vacation Planner for Tourism Regions

Taking a Preference SQL approach, a context-aware vacation planner for on-site activities is proposed to automatically generate vacation plans based on user preferences and situational aspects. Using different levels of abstraction, the result of the corresponding preference queries is always optimal and the result size is minimal. It consists of stereotype-specific and contextaware activities which are combined to create daily or even multi-day plans of activities. The correctness, completeness and optimality are assured by a preference calculus of strict partial orders. User preferences are initially collected and defined by a feedback questionnaire. The application is modelled by adequate preference compositions and the Preference SQL runtime system efficiently evaluates the resulting preference queries. The prototype proves that soft runtime requirements are met. Initial tests with real data from the industry-leading outdooractive platform indicate that the database-driven preference technology can successfully be employed to provide added value for vacation planning

Practical Preference Relations for Large Data Sets

User-defined preferences allow personalized ranking of query results. A user provides a declarative specification of his/her preferences, and the system is expected to use that specification to give more prominence to preferred answers. We study constraint formalisms for expressing user preferences as base facts in a partial order. We consider a language that allows comparison and a limited form of arithmetic, and show that the transitive closure computation required to complete the partial order terminates. We consider various ways of composing partial orders from smaller pieces, and provide results on the size of the resulting transitive closures. We introduce the notion of ``covering composition,'' which solves some semantic problems apparent in previous notions of composition. Finally, we show how preference queries within our language can be supported by suitable index structures for efficient evaluation over large data sets. Our results provide guidance about when complex preferences can be efficiently evaluated, and when they cannot