产品数据管理系统的用户权限管理

通过对产品数据管理系统的分析，本文探讨了产品数据管理系统中数据、工作流程、活动、操作和角色之间的关系，提出了基于数据、工作流程、活动、操作和角色的用户权限管理的建模方法。通过在某航空企业PDM系统中建立用户权限管理模型的应用，证明了这种方法具有简单、规范、有效等特点，井可广泛应用于其它类型的复杂信息系统中。     

Collaborative user modeling for enhanced content filtering in recommender systems

Recommender systems, which have emerged in response to the problem of information overload, provide users with recommendations of content suited to their needs. To provide proper recommendations to users, personalized recommender systems require accurate user models of characteristics, preferences and needs. In this study, we propose a collaborative approach to user modeling for enhancing personalized recommendations to users. Our approach first discovers useful and meaningful user patterns, and then enriches the personal model with collaboration from other similar users. In order to evaluate the performance of our approach, we compare experimental results with those of a probabilistic learning model, a user model based on collaborative filtering approaches, and a vector space model. We present experimental results that show how our model performs better than existing alternatives.     

Numerical uncertainty management in user and student modeling: An overview of systems and issues

A rapidly growing number of user and student modeling systems have employed numerical techniques for uncertainty management. The three major paradigms are those of Bayesian networks, the Dempster-Shafer theory of evidence, and fuzzy logic. In this overview, each of the first three main sections focuses on one of these paradigms. It first introduces the basic concepts by showing how they can be applied to a relatively simple user modeling problem. It then surveys systems that have applied techniques from the paradigm to user or student modeling, characterizing each system within a common framework. The final main section discusses several aspects of the usability of these techniques for user or student modeling, such as their knowledge engineering requirements, their need for computational resources, and the communicability of their results.     

一种面向个性化服务的客户端细粒度用户建模方法

用户建模是实现个性化服务的关键技术。本文分析了二类用户建模存在的问题，给出了细粒度用户模型的定义，结合用户的背景知识，提出了一种客户端细粒度用户建模方法 。采用词频方法选择的特征子集和改进的k近邻分类器构成用户模型。本文的细粒度用户建模方法不需要用户的频繁交互．也不必对用户兴趣作推测，具有更好的系统亲和力
和性能。实验表明，当特征个数为40时，构建的细粒度用户模型的分类精度可达90％以上；在细粒度用户模型中，大量的特征对用户模型没有意义。     

Mediation of user models for enhanced personalization in recommender systems

Provision of personalized recommendations to users requires accurate modeling of their interests and needs. This work proposes a general framework and specific methodologies for enhancing the accuracy of user modeling in recommender systems by importing and integrating data collected by other recommender systems. Such a process is defined as user models mediation. The work discusses the details of such a generic user modeling mediation framework. It provides a generic user modeling data representation model, demonstrates its compatibility with existing recommendation techniques, and discusses the general steps of the mediation. Specifically, four major types of mediation are presented: cross-user, cross-item, cross-context, and cross-representation. Finally, the work reports the application of the mediation framework and illustrates it with practical mediation scenarios. Evaluations of these scenarios demonstrate the potential benefits of user modeling data mediation, as in certain conditions it allows improving the quality of the recommendations provided to the users.

Adaptive Hypermedia

Adaptive hypermedia is a relatively new direction of research on the crossroads of hypermedia and user modeling. Adaptive hypermedia systems build a model of the goals, preferences and knowledge of each individual user, and use this model throughout the interaction with the user, in order to adapt to the needs of that user. The goal of this paper is to present the state of the art in adaptive hypermedia at the eve of the year 2000, and to highlight some prospects for the future. This paper attempts to serve both the newcomers and the experts in the area of adaptive hypermedia by building on an earlier comprehensive review (Brusilovsky, 1996; Brusilovsky, 1998).     

Adaptability Feature''''s Concept, Modeling and Application in Product Design

1 Introduction In practical, commonly the component structure design needs to begin from assemble. During the early design phase, it requires an initial correlation definition and configuration form definition for those important components and the spatial orientation layout design. In the following stages, the component structure details are gradual refined based on those pre-defined constraints and layout scheme, e.g. hole-and-cylinder mating, slot-and-key coupling etc. The design scheme ne…     

Constructing and Utilizing a Model of User Preferences in Collaborative Consultation Dialogues

A natural language collaborative consultation system must take user preferences into account. A model of user preferences allows a system to appropriately evaluate alternatives using criteria of importance to the user. Additionally, decision research suggests both that an accurate model of user preferences could enable the system to improve a user's decision-making by ensuring that all important alternatives are considered, and that such a model of user preferences must be built dynamically by observing the user's actions during the decision-making process. This paper presents two strategies: one for dynamically recognizing user preferences during the course of a collaborative planning dialogue and the other for exploiting the model of user preferences to detect suboptimal solutions and suggest better alternatives. Our recognition strategy utilizes not only the utterances themselves but also characteristics of the dialogue in developing a model of user preferences. Our generation strategy takes into account both the strength of a preference and the closeness of a potential match in evaluating actions in the user's plan and suggesting better alternatives. By modeling and utilizing user preferences, our system is able to fulfill its role as a collaborative agent.     

The um toolkit for cooperative user modelling

This paper gives an overview of the um toolkit: the philosophy underlying its design, examples of its use and discussion of the way it deals with some major issues in creating user modelling shells. The um toolkit has been developed to provide support for a variety of cooperative agents. An important element of its cooperativeness is due to its capacity to give users an understanding of their own user models. This paper describes two substantial but very different uses of the toolkit. The first involves a collection of coaching systems that help users learn more about their text editor. Experimental results suggest that the user model is associated with users learning more. The second is a movie advisor that uses a range of tools to construct and refine the user model and to filter a database of movies. Both these systems are built from combining tools in um. The paper describes several of the tools for constructing and refining user models. In addition it describes the user-model viewing tools and the way that these help users ensure their user models are correct. The paper also discusses the two central themes of the um work, the application of a tools approach to the design of a user modelling toolkit and the implications of making the user model accessible to its owner, the person modelled.     

Adaptation in Multimedia Systems

Multimedia systems can profit a lot from personalization. Such a personalization is essential to give users the feeling that the system is easily accessible especially if it is done automatically. The way this adaptive personalization works is very dependent on the adaptation model that is chosen.We introduce a generic two-dimensional classification framework for user modeling systems. This enables us to clarify existing as well as new applications in the area of user modeling. In order to illustrate our framework we evaluate push and pull based user modeling in user modeling systems.Paul de Vrieze received his Masters degree in Information Science in 2002 from the University Of Tilburg, The Netherlands. He is currently junior researcher at the University of Nijmegen. His main research interests include adaptive systems and user modelling.Patrick van Bommel received his Masters degree in Computer Science in 1990, and the degree of Ph.D in Mathematics and Computer Science, from the University of Nijmegen, the Netherlands in 1995. He is currently assistant professor at the University of Nijmegen. His main research interests include information modelling and information retrieval.Prof.Dr.Ir. Th.P. van der Weide received his masters degree from the Technical University Eindhoven, the Netherlands in 1975, and the degree of Ph.D in Mathematics and Physics from the University of Leiden, the Netherlands in 1980. He is currently professor at the University of Nijmegen, the Netherlands. His main research interests include information systems, information retrieval, hypertext and knowledge based systems.     

A Review and Analysis of Commercial User Modeling Servers for Personalization on the World Wide Web

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.     

The user modeling shell system BGP-MS

BGP-MS is a user modeling shell system that can assist interactive software systems in adapting to their current users by taking the users' presumed knowledge, beliefs, and goals into account. It offers applications several methods for communicating observations concerning the user to BGP-MS, and for obtaining information on currently held assumptions about the user from BGP-MS. It provides a choice of two integrated formalisms for representing beliefs and goals, and includes several types of inferences for drawing additional assumptions based on an initial interview, observed user actions, and stereotypical knowledge about pre-defined user subgroups. BGP-MS is a customizable software system that is independent from applications, operates concurrently with them, and interacts with them through inter-process communication. For tailoring BGP-MS to a specific application domain, the developer must select those components of BGP-MS that are needed in this domain and fill them with relevant domain-dependent user modeling knowledge. This paper first summarizes the user modeling services that BGP-MS provides to application programs at runtime. It discusses the representational and inferential foundations that determine the scope and the limits of these services, and also gives a detailed example illustrating the interaction between the various system components. It describes interfaces that are available to application developers for tailoring BGP-MS to the specific user modeling needs of their application domains. Finally, it compares the system with all other major user modeling shell systems, and describes a first application that employs BGP-MS for adapting hypertext to users' terminological knowledge.The managing UMUAI editor for this paper was Sandra Carberry, University of Delaware.     

个性化服务中的用户建模技术

作为个性化服务的基础和核心,用户建模的质量直接关系到个性化服务的质量.文章将用户建模的过程分为5个关键模块:输入、输出、建模时间、建模的对象、建模算法,并围绕这5个方面,对用户建模当前的研究现状、所面临的关键议题进行了系统的论述.其中,输入模块为用户模型的建立提供了必要的数据源,输出模块则描述用户模型的表示方式,建模时间描述了建模的时间长度和更新方式,建模的对象描述了对谁进行建模,建模算法则描述了几种典型的建模方法.最后对用户建模的技术发展进行了展望.     

A Movie Recommendation System – An Application of Voting Theory in User Modeling

Our research agenda focuses on building software agents that can employ user modeling techniques to facilitate information access and management tasks. Personal assistant agents embody a clearly beneficial application of intelligent agent technology. A particular kind of assistant agents, recommender systems, can be used to recommend items of interest to users. To be successful, such systems should be able to model and reason with user preferences for items in the application domain. Our primary concern is to develop a reasoning procedure that can meaningfully and systematically tradeoff between user preferences. We have adapted mechanisms from voting theory that have desirable guarantees regarding the recommendations generated from stored preferences. To demonstrate the applicability of our technique, we have developed a movie recommender system that caters to the interests of users. We present issues and initial results based on experimental data of our research that employs voting theory for user modeling, focusing on issues that are especially important in the context of user modeling. We provide multiple query modalities by which the user can pose unconstrained, constrained, or instance-based queries. Our interactive agent learns a user model by gaining feedback aboutits recommended movies from the user. We also provide pro-active information gathering to make user interaction more rewarding. In the paper, we outline the current status of our implementation with particular emphasis on the mechanisms used to provide robust and effective recommendations.     

Ontology-Based User Modeling in an Augmented Audio Reality System for Museums

Ubiquitous computing is a challenging area that allows us to further our understanding and techniques of context-aware and adaptive systems. Among the challenges is the general problem of capturing the larger context in interaction from the perspective of user modeling and human–computer interaction (HCI). The imperative to address this issue is great considering the emergence of ubiquitous and mobile computing environments. This paper provides an account of our addressing the specific problem of supporting functionality as well as the experience design issues related to museum visits through user modeling in combination with an audio augmented reality and tangible user interface system. This paper details our deployment and evaluation of ec(h)o – an augmented audio reality system for museums. We explore the possibility of supporting a context-aware adaptive system by linking environment, interaction objects and users at an abstract semantic level instead of at the content level. From the user modeling perspective ec(h)o is a knowledge-based recommender system. In this paper we present our findings from user testing and how our approach works well with an audio and tangible user interface within a ubiquitous computing system. We conclude by showing where further research is needed.     

Expert systems in manufacturing: An experience in Mexico

This article describes the experience of our research team in developing expert systems in the area of manufacturing for an industrial corporation in Mexico. It presents the lessons we have learned in introducing expert systems into the firm, selecting problem domains, acquiring and modeling knowledge, programming and testing prototypes, deploying systems in production, and estimating the benefits of their usage.     

Recommender Systems Research: A Connection-Centric Survey

Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from such a perspective. This viewpoint is under-emphasized in the recommender systems literature. We therefore take a connection-oriented perspective toward recommender systems research. We posit that recommendation has an inherently social element and is ultimately intended to connect people either directly as a result of explicit user modeling or indirectly through the discovery of relationships implicit in extant data. Thus, recommender systems are characterized by how they model users to bring people together: explicitly or implicitly. Finally, user modeling and the connection-centric viewpoint raise broadening and social issues—such as evaluation, targeting, and privacy and trust—which we also briefly address.     

笔式用户界面开发工具研究

笔式用户界面提供给用户更为自然的交互方式,然而,笔式用户界面的构造是一项非常困难的工作,一个可用的笔式用户界面系统往往需要多领域、多学科的知识.系统地论述了一个支持笔式用户界面开发的工具系统Penbuilder的设计实现.它基于笔交互的特性以及无处不在的计算环境的要求而设计,为笔式用户界面的开发提供高级的支持.基于Penbuilder的支持,设计开发了一批典型的笔式用户界面原型系统.该研究为笔式用户界面的构造与快速原型提供了有力的支持.     

Information Filtering: Overview of Issues,Research and Systems

An abundant amount of information is created and delivered over electronic media. Users risk becoming overwhelmed by the flow of information, and they lack adequate tools to help them manage the situation. Information filtering (IF) is one of the methods that is rapidly evolving to manage large information flows. The aim of IF is to expose users to only information that is relevant to them. Many IF systems have been developed in recent years for various application domains. Some examples of filtering applications are: filters for search results on the internet that are employed in the Internet software, personal e-mail filters based on personal profiles, listservers or newsgroups filters for groups or individuals, browser filters that block non-valuable information, filters designed to give children access them only to suitable pages, filters for e-commerce applications that address products and promotions to potential customers only, and many more. The different systems use various methods, concepts, and techniques from diverse research areas like: Information Retrieval, Artificial Intelligence, or Behavioral Science. Various systems cover different scope, have divergent functionality, and various platforms. There are many systems of widely varying philosophies, but all share the goal of automatically directing the most valuable information to users in accordance with their User Model, and of helping them use their limited reading time most optimally. This paper clarifies the difference between IF systems and related systems, such as information retrieval (IR) systems, or Extraction systems. The paper defines a framework to classify IF systems according to several parameters, and illustrates the approach with commercial and academic systems. The paper describes the underlying concepts of IF systems and the techniques that are used to implement them. It discusses methods and measurements that are used for evaluation of IF systems and limitations of the current systems. In the conclusion we present research issues in the Information Filtering research arena, such as user modeling, evaluation standardization and integration with digital libraries and Web repositories.