User Modeling

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Alfred Kobsa - One of the best experts on this subject based on the ideXlab platform.

  • generic User Modeling systems
    The adaptive web, 2007
    Co-Authors: Alfred Kobsa
    Abstract:

    This chapter reviews research results in the field of Generic User Modeling Systems. It describes the purposes of such systems, their services within User-adaptive systems, and the different design requirements for research prototypes and commercial deployments. It discusses the architectures that have been explored so far, namely shell systems that form part of the application, central server systems that communicate with several applications, and possible future agent-based User Modeling systems. Major implemented research prototypes and commercial systems are briefly described.

  • An LDAP-based User Modeling Server and its Evaluation
    User Modeling and User-Adapted Interaction, 2006
    Co-Authors: Alfred Kobsa, Josef Fink
    Abstract:

    Representation components of User Modeling servers have been traditionally based on simple file structures and database systems. We propose directory systems as an alternative, which offer numerous advantages over the more traditional approaches: international vendor-independent standardization, demonstrated performance and scalability, dynamic and transparent management of distributed information, built-in replication and synchronization, a rich number of pre-defined types of User information, and extensibility of the core representation language for new information types and for data types with associated semantics. Directories also allow for the virtual centralization of distributed User models and their selective centralized replication if better performance is needed. We present UMS, a User Modeling server that is based on the Lightweight Directory Access Protocol (LDAP). UMS allows for the representation of different models (such as User and usage profiles, and system and service models), and for the attachment of arbitrary components that perform User Modeling tasks upon these models. External clients such as User-adaptive applications can submit and retrieve information about Users. We describe a simulation experiment to test the runtime performance of this server, and present a theory of how the parameters of such an experiment can be derived from empirical web usage research. The results show that the performance of UMS meets the requirements of current small and medium websites already on very modest hardware platforms, and those of very large websites in an entry-level business server configuration.

  • User Modeling - Performance evaluation of User Modeling servers under real-world workload condition
    User Modeling 2003, 2003
    Co-Authors: Alfred Kobsa, Josef Fink
    Abstract:

    Before User Modeling servers can be deployed to real-world application environments with potentially millions of Users, their runtime behavior must be experimentally verified under realistic workload conditions to ascertain their satisfactory performance in the target domain. This paper discusses performance experiments which systematically vary the number of profiles available in the User Modeling server, and the frequency of page requests that simulated Users submit to a hypothetical personalized website. The parameters of this simulation are based on empirical web usage research. For small to medium sized test scenarios, the processing time for a representative mix of User Modeling operations was found to only degressively increase with the frequency of page requests. The distribution of the User Modeling server across a network of computers additionally accelerated those operations that are amenable to parallel execution. A large-scale test with several million active User profiles and a page request rate that is representative of major websites confirmed that the User Modeling performance of our server will not impose a significant overhead for a personalized website. It also corroborated our earlier finding that directories provide a superior foundation for User Modeling servers than traditionally used data bases and knowledge bases.

  • User Modeling for Personalized City Tours
    Artificial Intelligence Review, 2002
    Co-Authors: Josef Fink, Alfred Kobsa
    Abstract:

    Several current support systems for travel and tourism are aimed at providing information in a personalized manner, taking Users' interests and preferences into account. In this vein, personalized systems observe Users' behavior and, based thereon, make generalizations and predictions about them. This article describes a User Modeling server that offers services to personalized systems with regard to the analysis of User actions, the representation of assumptions about the User, and the inference of additional assumptions based on domain knowledge and characteristics of similar Users. The system is open and compliant with major standards, allowing it to be easily accessed by clients that need personalization services.

  • generic User Modeling systems
    User Modeling and User-adapted Interaction, 2001
    Co-Authors: Alfred Kobsa
    Abstract:

    The paper reviews the development of generic User Modeling systems over the past twenty years. It describes their purposes, their services within User-adaptive systems, and the different design requirements for research prototypes and commercially deployed servers. It discusses the architectures that have been explored so far, namely shell systems that form part of the application, central server systems that communicate with several applications, and possible future User Modeling agents that physically follow the User. Several implemented research prototypes and commercial systems are briefly described.

Peter Brusilovsky - One of the best experts on this subject based on the ideXlab platform.

  • Towards User Modeling meta-ontology
    Lecture Notes in Computer Science, 2020
    Co-Authors: Michael Yudelson, Tatiana Gavrilova, Peter Brusilovsky
    Abstract:

    The paper proposes meta-ontology of the User Modeling field. Ontology is meant to structure the state-of-the-art in the field and serve as a central reference point and as a tool to index systems, papers and learning media. Such ontology is beneficial for both the User Modeling research community and the students as it creates a shared conceptualization of the known approaches to building User models and their implementations.

  • User Modeling - A User Modeling Server for Contemporary Adaptive Hypermedia: An Evaluation of the Push Approach to Evidence Propagation
    User Modeling 2007, 2007
    Co-Authors: Michael Yudelson, Peter Brusilovsky, Vladimir Zadorozhny
    Abstract:

    Despite the growing popularity of User Modeling servers, little attention has been paid to optimizing and evaluating the performance of these servers. We argue that implementation issues and their influence on server performance should become the central focus of the User Modeling community, since there is a sharply increasing real-life load on User Modeling servers, This paper focuses on a specific implementation-level aspect of User Modeling servers --- the choice of pushor pullapproaches to evidence propagation. We present a new push-based implementation of our User Modeling server CUMULATE and compare its performance with the performance of the original pull-based CUMULATE server.

  • User Modeling - Towards User Modeling meta-ontology
    User Modeling 2005, 2005
    Co-Authors: Michael Yudelson, Tatiana Gavrilova, Peter Brusilovsky
    Abstract:

    The paper proposes meta-ontology of the User Modeling field. Ontology is meant to structure the state-of-the-art in the field and serve as a central reference point and as a tool to index systems, papers and learning media. Such ontology is beneficial for both the User Modeling research community and the students as it creates a shared conceptualization of the known approaches to building User models and their implementations.

  • User Modeling in a distributed e learning architecture
    Lecture Notes in Computer Science, 2005
    Co-Authors: Peter Brusilovsky, Sergey Sosnovsky, Olena Shcherbinina
    Abstract:

    This paper is focused on User Modeling and adaptation in distributed E-Learning systems. We describe here CUMULATE, a generic student Modeling server developed for a distributed E-Learning architecture, KnowledgeTree. We also introduce a specific, topic-based knowledge Modeling approach which has been implemented as an inference agent in CUMULATE and used in QuizGuide, an adaptive system that helps students select the most relevant self-assessment quizzes. We also discuss our attempts to evaluate this multi-level student Modeling.

  • Preface to Special Issue on User Modeling for Web Information Retrieval
    User Modeling and User-Adapted Interaction, 2004
    Co-Authors: Peter Brusilovsky, Carlo Tasso
    Abstract:

    Presents preface to the special issue on 'User Modeling for Web Information Retrieval'. Information access is one of the hottest topics of information society and it has become even more important since the advent of the Web. However, the process of accessing what is 'relevant' is very difficult, time-consuming, and in many cases practically unfeasible, since it requires huge cognitive processing, which is out of range for our limited mental resources, energy, and time. This state of the art requires new innovative tools for information retrieval on the Web. Importance and role of User Modeling and adaptive personalization are straight forward. Equipped with User Modeling tools capable of comprehending specific User information needs, the new retrieval tools will be able to effectively filter out irrelevant information, to rank information in the most suitable way, to compare the contents of different documents, to personalize information presentation, and to adequately tailor man-machine interaction. Reaching this ambitious goal is not easy. The papers included in this Special Issue show four different relevant paths to build innovative personalized tools capable of identifying and selecting the right and relevant information, in the right moment, without waste of time and cognitive activities. (PsycINFO Database Record (c) 2007 APA, all rights reserved)

Maria Virvou - One of the best experts on this subject based on the ideXlab platform.

  • Smart Tourism Through Social Network User Modeling: A Literature Review
    2018 9th International Conference on Information Intelligence Systems and Applications (IISA), 2018
    Co-Authors: Aristea Kontogianni, Katerina Kabassi, Maria Virvou, Efthimios Alepis
    Abstract:

    In an era of big data and smart cities, the need to adapt digital content to Users' preferences and personality has become more demanding. As the tourism sector attracts more attention, numerous smart tourism applications are proposed that aim to harness the power of social media analytics in order to offer personalized User Experience (UX) to their Users and enrich tourist experience. This paper focuses on presenting a literature review on research articles that focus on both User Modeling via social media and smart tourism, so as to set the ground for further research in the combination of these two fields and discuss about future challenges for smart tourism through social network User Modeling.

  • IISA - Smart Tourism Through Social Network User Modeling: A Literature Review
    2018 9th International Conference on Information Intelligence Systems and Applications (IISA), 2018
    Co-Authors: Aristea Kontogianni, Katerina Kabassi, Maria Virvou, Efthimios Alepis
    Abstract:

    In an era of big data and smart cities, the need to adapt digital content to Users' preferences and personality has become more demanding. As the tourism sector attracts more attention, numerous smart tourism applications are proposed that aim to harness the power of social media analytics in order to offer personalized User Experience (UX) to their Users and enrich tourist experience. This paper focuses on presenting a literature review on research articles that focus on both User Modeling via social media and smart tourism, so as to set the ground for further research in the combination of these two fields and discuss about future challenges for smart tourism through social network User Modeling.

  • User Modeling Framework: The Case of Multi-language and Mathematics Learning
    2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2012
    Co-Authors: Maria Virvou, Christos Troussas, Sotirios-christos Sidiropoulos, Georgia Halmouki
    Abstract:

    In this paper we describe a framework for User Modeling in multi-language and mathematics learning. The basic idea of the proposed framework is to create student models in order to assist students in the simultaneous learning of multiple languages or mathematics. The system constructs an individual model for each student, which holds information about his/her knowledge level and the error proneness in the curriculum being taught. This framework is used to support each student while studying the theoretical section and getting evaluated. Furthermore, we describe the error diagnosis component, which tries to intelligently elicit information about the reason of a student error and builds accurately his/her individual profile. The tutoring component incorporates the order of teaching a curriculum or how to offer hints during problem solving. Finally, User Modeling uses information which emanates directly from students and operates in conjunction with error diagnosis and tutoring components in order to promote the educational process.

  • User Modeling on Communication Characteristics Using Machine Learning in Computer-Supported Collaborative Multiple Language Learning
    2012 IEEE 24th International Conference on Tools with Artificial Intelligence, 2012
    Co-Authors: Maria Virvou, Efthimios Alepis, Christos Troussas
    Abstract:

    Towards the creation of a multiple language learning environment which supports and enhances collaboration among its students we propose an approach that uses User Modeling and machine learning. The well known theory of User Modeling is used to collect User characteristics and as second step a classical machine learning approach is incorporated in order to intelligently use these characteristics to create student groups. The resulting student groups promote win-win collaboration, thus support the learning process and provide additional educational benefits for the learners.

  • Improving agent control for User Modeling
    Proceedings First International IEEE Symposium Intelligent Systems, 2002
    Co-Authors: Maria Virvou, Katerina Kabassi
    Abstract:

    This paper describes the User Modeling Agent (UM Agent) of an intelligent graphical User interface that manipulates files. The intelligent GUI is called IFM and it monitors Users while they work; in case a User has made a mistake, it intervenes automatically and offers advice. The reasoning of the UM Agent is largely based on an adaptation of a cognitive theory, called Human Plausible Reasoning (HPR). The UM Agent observes Users during their interaction with the system, maintains and manages the User profiles and provides relevant information whenever other agents request it. The main focus of this paper is on examining how the UM Agent's control can be improved by the combination of Human Plausible Reasoning and stereotypical knowledge.

Efthimios Alepis - One of the best experts on this subject based on the ideXlab platform.

  • Smart Tourism Through Social Network User Modeling: A Literature Review
    2018 9th International Conference on Information Intelligence Systems and Applications (IISA), 2018
    Co-Authors: Aristea Kontogianni, Katerina Kabassi, Maria Virvou, Efthimios Alepis
    Abstract:

    In an era of big data and smart cities, the need to adapt digital content to Users' preferences and personality has become more demanding. As the tourism sector attracts more attention, numerous smart tourism applications are proposed that aim to harness the power of social media analytics in order to offer personalized User Experience (UX) to their Users and enrich tourist experience. This paper focuses on presenting a literature review on research articles that focus on both User Modeling via social media and smart tourism, so as to set the ground for further research in the combination of these two fields and discuss about future challenges for smart tourism through social network User Modeling.

  • IISA - Smart Tourism Through Social Network User Modeling: A Literature Review
    2018 9th International Conference on Information Intelligence Systems and Applications (IISA), 2018
    Co-Authors: Aristea Kontogianni, Katerina Kabassi, Maria Virvou, Efthimios Alepis
    Abstract:

    In an era of big data and smart cities, the need to adapt digital content to Users' preferences and personality has become more demanding. As the tourism sector attracts more attention, numerous smart tourism applications are proposed that aim to harness the power of social media analytics in order to offer personalized User Experience (UX) to their Users and enrich tourist experience. This paper focuses on presenting a literature review on research articles that focus on both User Modeling via social media and smart tourism, so as to set the ground for further research in the combination of these two fields and discuss about future challenges for smart tourism through social network User Modeling.

  • User Modeling on Communication Characteristics Using Machine Learning in Computer-Supported Collaborative Multiple Language Learning
    2012 IEEE 24th International Conference on Tools with Artificial Intelligence, 2012
    Co-Authors: Maria Virvou, Efthimios Alepis, Christos Troussas
    Abstract:

    Towards the creation of a multiple language learning environment which supports and enhances collaboration among its students we propose an approach that uses User Modeling and machine learning. The well known theory of User Modeling is used to collect User characteristics and as second step a classical machine learning approach is incorporated in order to intelligently use these characteristics to create student groups. The resulting student groups promote win-win collaboration, thus support the learning process and provide additional educational benefits for the learners.

Josef Fink - One of the best experts on this subject based on the ideXlab platform.

  • An LDAP-based User Modeling Server and its Evaluation
    User Modeling and User-Adapted Interaction, 2006
    Co-Authors: Alfred Kobsa, Josef Fink
    Abstract:

    Representation components of User Modeling servers have been traditionally based on simple file structures and database systems. We propose directory systems as an alternative, which offer numerous advantages over the more traditional approaches: international vendor-independent standardization, demonstrated performance and scalability, dynamic and transparent management of distributed information, built-in replication and synchronization, a rich number of pre-defined types of User information, and extensibility of the core representation language for new information types and for data types with associated semantics. Directories also allow for the virtual centralization of distributed User models and their selective centralized replication if better performance is needed. We present UMS, a User Modeling server that is based on the Lightweight Directory Access Protocol (LDAP). UMS allows for the representation of different models (such as User and usage profiles, and system and service models), and for the attachment of arbitrary components that perform User Modeling tasks upon these models. External clients such as User-adaptive applications can submit and retrieve information about Users. We describe a simulation experiment to test the runtime performance of this server, and present a theory of how the parameters of such an experiment can be derived from empirical web usage research. The results show that the performance of UMS meets the requirements of current small and medium websites already on very modest hardware platforms, and those of very large websites in an entry-level business server configuration.

  • User Modeling - Performance evaluation of User Modeling servers under real-world workload condition
    User Modeling 2003, 2003
    Co-Authors: Alfred Kobsa, Josef Fink
    Abstract:

    Before User Modeling servers can be deployed to real-world application environments with potentially millions of Users, their runtime behavior must be experimentally verified under realistic workload conditions to ascertain their satisfactory performance in the target domain. This paper discusses performance experiments which systematically vary the number of profiles available in the User Modeling server, and the frequency of page requests that simulated Users submit to a hypothetical personalized website. The parameters of this simulation are based on empirical web usage research. For small to medium sized test scenarios, the processing time for a representative mix of User Modeling operations was found to only degressively increase with the frequency of page requests. The distribution of the User Modeling server across a network of computers additionally accelerated those operations that are amenable to parallel execution. A large-scale test with several million active User profiles and a page request rate that is representative of major websites confirmed that the User Modeling performance of our server will not impose a significant overhead for a personalized website. It also corroborated our earlier finding that directories provide a superior foundation for User Modeling servers than traditionally used data bases and knowledge bases.

  • User Modeling for Personalized City Tours
    Artificial Intelligence Review, 2002
    Co-Authors: Josef Fink, Alfred Kobsa
    Abstract:

    Several current support systems for travel and tourism are aimed at providing information in a personalized manner, taking Users' interests and preferences into account. In this vein, personalized systems observe Users' behavior and, based thereon, make generalizations and predictions about them. This article describes a User Modeling server that offers services to personalized systems with regard to the analysis of User actions, the representation of assumptions about the User, and the inference of additional assumptions based on domain knowledge and characteristics of similar Users. The system is open and compliant with major standards, allowing it to be easily accessed by clients that need personalization services.

  • a review and analysis of commercial User Modeling servers for personalization on the world wide web
    User Modeling and User-adapted Interaction, 2000
    Co-Authors: Josef Fink, Alfred Kobsa
    Abstract:

    The aim of this article is to present and discuss selected commercial User Modeling systems against the background of deployment requirements in real-world environments. Following the recent trend towards personalization on the World Wide Web, these systems are mainly aimed at supporting e-commerce including customer relationship management. In order to guide and structure our review, we define a requirements catalogue that comprises the main dimensions of functionality, data acquisition, representation, extensibility and flexibility, integration of external User-related information, compliance with standards, concern for privacy, and system architecture. Apart from the novelty of such a comparison both inside and outside the classical User Modeling literature, a presentation of the core features of these commercial systems may provide a source of information and inspiration for the design, implementation, and deployment of future User Modeling systems in research and commercial environments.

  • Transactional consistency in User Modeling systems
    CISM International Centre for Mechanical Sciences, 1999
    Co-Authors: Josef Fink
    Abstract:

    It is widely accepted that the consistency of adaptive interfaces is crucial for their usability. Many threats for consistency in adaptive applications have been reported in the literature so far (e.g., consistency of adaptation methods and techniques, consistency of the User model). In this paper we argue that many, if not all, User Modeling systems that have been developed so far are substantially threatening consistency by offering no adequate means for communicating consistency contexts. This is especially the case for User Modeling servers, which are supposed to serve several applications in parallel. In order to prevent consistency problems in User Modeling systems, we introduce basic concepts and techniques from transaction management. User Modeling systems that adhere to the principles of transaction management can be expected to provide a reliable source of User information for adaptive applications, especially in real world settings.