Learning About the User – User Modeling and Machine Learning
نویسنده
چکیده
User modeling is employed by applications that need to maintain explicit models of their users in order to exhibit individualized behaviour. The user modeling task involves representation and acquisition of assumptions about the user. Particularly user model acquisition is closely related to the machine learning task of automatically acquiring new information as well as new representations of existing information. This paper shows how and for which purposes machine learning techniques have been and could be employed in user modeling. Also usage modeling, a more action-centered approach to user modeling, is considered. Finally, the LaboUr approach to user modeling is sketched, which regards user modeling as learning problem.
منابع مشابه
Trust Classification in Social Networks Using Combined Machine Learning Algorithms and Fuzzy Logic
Social networks have become the main infrastructure of today’s daily activities of people during the last decade. In these networks, users interact with each other, share their interests on resources and present their opinions about these resources or spread their information. Since each user has a limited knowledge of other users and most of them are anonymous, the trust factor plays an import...
متن کاملSimilarity measurement for describe user images in social media
Online social networks like Instagram are places for communication. Also, these media produce rich metadata which are useful for further analysis in many fields including health and cognitive science. Many researchers are using these metadata like hashtags, images, etc. to detect patterns of user activities. However, there are several serious ambiguities like how much reliable are these informa...
متن کاملImproving the performance of recommender systems in the face of the cold start problem by analyzing user behavior on social network
The goal of recommender system is to provide desired items for users. One of the main challenges affecting the performance of recommendation systems is the cold-start problem that is occurred as a result of lack of information about a user/item. In this article, first we will present an approach, uses social streams such as Twitter to create a behavioral profile, then user profiles are clusteri...
متن کاملMachine Learning and Citizen Science: Opportunities and Challenges of Human-Computer Interaction
Background and Aim: In processing large data, scientists have to perform the tedious task of analyzing hefty bulk of data. Machine learning techniques are a potential solution to this problem. In citizen science, human and artificial intelligence may be unified to facilitate this effort. Considering the ambiguities in machine performance and management of user-generated data, this paper aims to...
متن کاملLearning-Based Energy Management System for Scheduling of Appliances inside Smart Homes
Improper designs of the demand response programs can lead to numerous problems such as customer dissatisfaction and lower participation in these programs. In this paper, a home energy management system is designed which schedules appliances of smart homes based on the user’s specific behavior to address these issues. Two types of demand response programs are proposed for each house which are sh...
متن کاملWeb pages ranking algorithm based on reinforcement learning and user feedback
The main challenge of a search engine is ranking web documents to provide the best response to a user`s query. Despite the huge number of the extracted results for user`s query, only a small number of the first results are examined by users; therefore, the insertion of the related results in the first ranks is of great importance. In this paper, a ranking algorithm based on the reinforcement le...
متن کامل