the main purpose of this study is to investigate the preferences of urban dwellers for variouselements of urban parks in order to provide some important suggestions for rehabilitation of urban deficient parks. inthis regard, this study has conducted a survey in one of the oldest parks in khorramabad, iran, to reveal the overallsatisfaction of the park situation and to explore the preferences of...

This chapter introduces the concept of improving student memory retention using a distance learning tool by establishing the student’s communication preference and learning style before the student uses the module contents. It argues that incorporating a distance learning tool with an intelligent/interactive tutoring system using various components (psychometric tests, communication preference ...

Although there is existing work on learning user preferences in various systems, the outputs of such systems tend to be confusing to users. Studies of users interacting with such systems show that when the system incorrectly predicts a user's preference, the user may attempt to correct the views of the system (for instance, by randomly providing more training examples). In many cases, however, ...

PrefWork is a framework for testing of methods of induction of user preferences. PrefWork is thoroughly described in this paper. A reader willing to use PrefWork finds here all necessary information sample code, configuration files and results of the testing are presented in the paper. Related approaches for data mining testing are compared to our approach. There is no software available specia...

In previous work [8] we presented a casebased approach to eliciting and reasoning with preferences. A key issue in this approach is the definition of similarity between user preferences. We introduced the probabilistic distance as a measure of similarity on user preferences, and provided an algorithm to compute the distance between two partially specified value functions. This is for the case o...

Customer preference learning and recommendation for (e-)commerce is a widely researched problem where a number of different solutions have been proposed. In this study we propose and implement a novel approach to the problem of extracting and modelling user preferences in commerce using latent topic models. We explore the use of probabilistic topic models on transaction itemsets considering bot...

When searching for configurable products, helping users to state their preferences is a crucial task. It involves helping users to understand the space of feasible configurations to decide on realistic preferences. However, many computer tools do not afford users to adequately focus on fundamental decision objectives, reveal hidden preferences, revise conflicting preferences, or explicitly reas...