Identifying expertise markers in routine work artifacts: exploring micronote taking behavior

Identifying expertise within an organization is a critical component of any knowledge management effort. It is, however, an exceptionally resource intensive activity that is difficult to initiate and problematic to maintain. The development of experimental expertise recommender systems has prompted innovative research into the use of expertise markers found on routine information artifacts. Particular classes of information artifacts have been identified as rich possible sources for expertise markers. This paper hypothesizes about the potential for leveraging another class of artifacts, “micronotes”, which are our ubiquitous, personal jottings of notable information. Lacking usable digital support, these are currently opaque to organizational memory systems, but may be central to our natural expertise mapping abilities. A field study designed to explore natural micronote taking behaviors is described and early findings are discussed. Implications for improving the design of mobile computing support to integrate micronotes into expertise mapping activities are also presented.     

A knowledge-based approach to design for manufacturability

In the light of growing global competition, organizations around the world today are constantly under pressure to produce high-quality products at an economical price. The integration of design and manufacturing activities into one common engineering effort has been recognized as a key strategy for survival and growth. Design for manufacturability (DFM) is an approach to design that fosters the simultaneous involvement of product design and process design. The implementation of the DFM approach requires the collaboration of both the design and manufacturing functions within an organization. Many reasons can be cited for the inability to implement the DFM approach effectively, including: lack of interdisciplinary expertise of designers; inflexibility in organizational structure, which hinders interaction between design and manufacturing functions; lack of manufacturing cost information at the design phase; and absence of integrated engineering effort intended to maximize functional and manufacturability objectives. The purpose of this research is to show how expert systems methodology could be used to provide manufacturability expertise during the design phase of a product. An object- and rule-based expert system has been developed that has the capability: (1) to make process selection decisions based on a set of design and production parameters to achieve cost-effective manufacture; and (2) to estimate manufacturing cost based on the identified processes. The expertise for primary process selection is developed for casting and forging processes. The specialized processes considered are die casting, investment casting, sand casting, precision forging, open die forging and conventional die forging. The processes considered for secondary process selection are end milling and drilling. The cost estimation expertise is developed for the die casting process, the milling and drilling operations, and the manual assembly operations. The results obtained from the application of the expert system suggest that the use of expert systems methodology is a feasible method for implementing the DFM approach.     

The infusion of expert systems in banking: An exploratory study

Numerous studies can be found on expert systems (ES) as a specific IT in the literature. However, their focus has been mainly on system development from a technical perspective. Based on an empirical study on expert systems diffusion in 20 British banking organizations, this paper reports the findings from the study. The study finds that ES infusion concentrated in specific processes that require extensive knowledge in banking. There is a strong organizational perspective towards expert systems development in these banking organizations rather than the technical perspective. ES diffusion and top management commitment are closely associated. The existence of IT strategy aligned with business strategy (and/or with an A1 element within it) is not a good predictor for ES adoptions. Three cases of expert systems applications in banking are given in the paper. These results are useful for practitioners in managing their intelligent systems projects and researchers for further studies in this area.     

An exploratory classification of applications in the realm of collaborative modeling and design

The high complexity and diversity of today’s design projects demands the participation of multiple experts. The participating experts can influence the design process by sharing their perspective, expertise and resources. The involvement of various experts is often known as collaborative modeling and design. A collaborative modeling environment can encompass various geographical or organizational boundaries. In this paper, we provide a classification to study various aspects of this important issue through the exploration of the existing models, methods and applications in this area. The paper further addresses both model-oriented and artifact-neutral collaboration approaches and enumerates their features. The paper introduces the features of and classifies several relevant applications. The classification can serve as a guideline for customizing a suitable setting for a collaborative modeling process based on given requirements, needs and demands. Several suggestions for future work are also provided.     

An approach to expert recommendation based on fuzzy linguistic method and fuzzy text classification in knowledge management systems

Since organizational tacit knowledge such as know-how and experiences usually resides in the owner’s brain, consulting the expert is an effective and efficient way to utilize this type of knowledge. However, users are no longer able to effectively find the appropriate experts in the knowledge management system due to the complexity and diversity of the expertise and the knowledge needs. In this paper, an approach to expert recommendation is proposed to assist the user to find the required experts. The method adopts the fuzzy linguistic method to construct the expert profile, that is, to model expert’s expertise. In addition, the fuzzy text classifier is used to get the relevant degree of the document to each knowledge area when the document is registered, which is the base of the following user profile construction. Then, the user profile consisting of the time and the relevance factors of the rated documents is constructed to derive the overall knowledge needs level of the user. Consequently, the expert that fulfills the knowledge needs most is recommended based on the similarity between the derived expert profile and the user profile. The developed prototype system, “knowledge management system in aircraft industry company”, is introduced and the experimental results show the proposed approach is feasible and effective.     

From means to ends: The transformation of ERP in a manufacturing company

In this paper, we present a case study of the restructuring of an Enterprise Resource Planning (ERP) system within a manufacturing company, in particular the combination of Material Requirement Planning (MRP) with a Just In Time (JIT) material management procedure at the assembly lines. We focus in this study upon the mutual shaping of technology and organizational culture, in particular the virtualization of the organization. It is argued that the implementation of ERP in this specific context was more than an adaptation of a standardized information system relative to organizational requirements, and that the organizational adaptations were more than a re-engineering of business processes relative to ERP. Instead, we suggest that in this case the ERP system itself has been transformed, including a change in the signification of ERP within the company.     

Enhancing security requirements engineering by organizational learning

More and more software projects today are security-related in one way or the other. Requirements engineers without expertise in security are at risk of overlooking security requirements, which often leads to security vulnerabilities that can later be exploited in practice. Identifying security-relevant requirements is labor-intensive and error-prone. In order to facilitate the security requirements elicitation process, we present an approach supporting organizational learning on security requirements by establishing company-wide experience resources and a socio-technical network to benefit from them. The approach is based on modeling the flow of requirements and related experiences. Based on those models, we enable people to exchange experiences about security-relevant requirements while they write and discuss project requirements. At the same time, the approach enables participating stakeholders to learn while they write requirements. This can increase security awareness and facilitate learning on both individual and organizational levels. As a basis for our approach, we introduce heuristic assistant tools. They support reuse of existing experiences that are relevant for security. In particular, they include Bayesian classifiers that issue a warning automatically when new requirements seem to be security-relevant. Our results indicate that this is feasible, in particular if the classifier is trained with domain-specific data and documents from previous projects. We show how the ability to identify security-relevant requirements can be improved using this approach. We illustrate our approach by providing a step-by-step example of how we improved the security requirements engineering process at the European Telecommunications Standards Institute (ETSI) and report on experiences made in this application.     

Rethinking competence systems for knowledge-based organizations

Existing competence systems are based on a rationalistic view of competence. While these competence systems might work in job-based organizations, we argue that in more dynamic settings, such as in knowledge-based organizations, the interest-informed actions that capture the emergent competencies of tomorrow require different types of information technology support. The main objective of this paper is to elaborate on the possibilities and implications of using interest-activated technology as a design rationale for competence systems. This paper is based on an action case study of an implemented interest-activated Intranet recommender system prototype at Volvo Information Technology AB in Gothenburg, Sweden. On the basis of how organizational members used this prototype to find information they were interested in, our research team was able to inquire into how personal interest, embodied in information-seeking activities, could be a means for identifying competence. Building on the relation between personal interest and competence, we discuss competence systems design and spell out explicit implications for managerial practice in knowledge-based organizations.     

Building an expert system for the design of sport shoes

This paper presents a module of the the framework of expert system for prototype shoe design which gives dimension setting, structural materials, form design and surface features based on user requirements. The development of inference rules for the proposed expert system is presented. Finally, problems encountered in this development process are discussed.     

An intelligent news recommender agent for filtering and categorizing large volumes of text corpus

This article presents an intelligent news recommender agent (INRA), which can be used to filter news articles as well as to recommend relevant news for individual user automatically. Three specific objectives underlie the presentation of the intelligent news recommender agent in this study. The first is to describe the basic architecture of this approach, and the second is to show the design of the fuzzy hierarchical mixture of the expert model for text categorization. The third and more elaborate goal is to show that the proposed system is able to perform a news‐recommending process. We show this approach with standard benchmark examples of the Reuters‐21578 in order to verify the effectiveness of news recommending. © 2004 Wiley Periodicals, Inc.     

Group Decision Making on Urban Planning Using Desktop Multimedia Conferencing

Recent developments on multimedia systems and networking technology show that using desktop multimedia conferencing for group decision making on wide area networks such as the Internet is possible. In this paper we review the design, hardware and software requirements and organizational issues in a desktop multimedia conferencing system. We draw on our experiences from multiple multimedia conferences on the Internet and in particular we focus on a case study on urban planning using desktop multimedia conferencing on the Internet. Further we discuss implications for further research on desktop multimedia conferencing.     

Experiments on user experiences with recommender interfaces

Recommender systems have been increasingly adopted as personalisation services in e-commerce. They facilitate users to locate items which they would be interested in viewing or purchasing. However, most studies have emphasised on the algorithm's performance, rather than on in-depth analysis of user experiences with the recommender interface. In this article, we report the results of two studies that compared two recommender interfaces: the organisation-based interface (where recommendations are presented in a category structure via the preference-based organisation method) and the standard ranked list (where recommendations are listed one after the other as ordered by their prediction scores).The first study focuses on evaluating users' eye-movement behaviour in these interfaces. With the help of an eye tracker, we found that the organisation interface (ORG) can significantly attract users' attentions to more recommended items. As a result, more users made product choices in that interface. The second, larger-scale, cross-cultural user survey further shows that the ORG performed significantly better in terms of enhancing users' perceived recommendation quality, perceived ease of use and perceived usefulness of the system. Hence, these empirical findings suggest that the change of recommender interface design can not only alter users' attention distribution, but also influence their subjective attitudes towards the system.     

Ergonomic criteria in large-scale engineering design--II. Evaluating and applying requirements in the real world of design.

Ergonomic standards to be used in engineering design are at present being developed throughout the world. However, not much is known about how ergonomic criteria function in an organizational setting. This study investigates how engineering designers in two large-scale engineering projects evaluate ergonomic criteria that are part of the design requirements in the projects. The designers state a clear preference for specific criteria. We also show how all design criteria are subject to organizational constraints, and that specific formulations are not a guarantee for the implementation of ergonomic criteria. Emphasising a few specific criteria might have an educational impact on the designers. The active involvement of an HF specialist is also critical to ensure a positive outcome for ergonomic criteria in the design negotiation process.     

Designing a visualization framework for multidimensional data

Interest in visualization has grown in recent years, producing rapid advances in the diversity of research and in the scope of proposed techniques. Much of the initial focus in computer-based visualization concentrated on display algorithms, often for specific domains. For example, volume, flow, and terrain visualization techniques have generated significant insights into fundamental graphics and visualization theory, aiding the application experts who use these techniques to advance their own research. More recent work has extended visualization to abstract data sets like network intrusion detection, recommender systems, and database query results. This article describes our initial end-to-end system that starts with data management and continues through assisted visualization design, display, navigation, and user interaction. The purposes of this discussion are to (i) promote a more comprehensive visualization framework; (ii) describe how to apply expertise from human psychophysics, databases, rational logic, and artificial intelligence to visualization; and (iii) illustrate the benefits of a more complete framework using examples from our own experiences.     

知识驱动的推荐系统：现状与展望

个性化推荐系统能够根据用户的个性化偏好和需要,自动、快速、精准地为用户提供其所需的互联网资源,已成为当今大数据时代应用最广泛的信息检索系统,具有巨大的商业应用价值。近年来,随着互联网海量数据的激增,人工智能技术的快速发展与普及,以知识图谱为代表的大数据知识工程日益受到学界和业界的高度关注,也有力地推动推荐系统和个性化推荐技术也迈入到知识驱动与赋能的发展阶段。将知识图谱中蕴含的丰富知识作为有用的辅助信息引入推荐系统,不仅能够有效应对数据稀疏、语义失配等传统推荐系统难以避免的问题,还能帮助推荐系统产生多样化、可解释的推荐结果,并更好地完成跨领域推荐、序列化推荐等具有挑战性的推荐任务,从而提升各类实际推荐场景中的用户满意度。本文将现有融入知识图谱的各种推荐模型按其采用的推荐算法与面向的推荐场景不同进行分类,构建科学、合理的分类体系。其中,按照推荐方法的不同,划分出基于特征表示的和基于图结构的两大类推荐模型;按推荐场景划分,特别关注多样化推荐、可解释推荐、序列化推荐与跨领域推荐。然后,我们在各类推荐模型中分别选取代表性的研究工作进行介绍,还简要对比了各个模型的特点与优劣。此外,本文还结合当下人工智能技术和应用的发展趋势,展望了认知智能推荐系统的发展前景,具体包括融合多模态知识的推荐系统,具有常识理解能力的推荐系统,以及解说式、劝说式、抗辩式推荐系统。本文的综述内容和展望可作为推荐系统未来研究方向的有益参考。     

Knowledge acquisition as a constructive modeling activity

Knowledge acquisition is a constructive modeling process, not simply a matter of “expertise transfer.” Consistent with this perspective, we advocate knowledge acquisition practices and tools that facilitate active collaboration between expert and knowledge engineer, that exploit a serviceable theory in their application, and that support knowledge-based system development from a life-cycle perspective. A constructivist theory of knowledge is offered as a plausible theoretical foundation for knowledge acquisition and as an effective practical approach to the dynamics of modeling. In this view, human experts construct knowledge from their own personal experiences while interacting with their social constituencies (e.g., supervisors, colleagues, clients patients) in their niche of expertise. Knowledge acquisition is presented as a cooperative enterprise in which the knowledge engineer and expert collaborate in constructing an explicit model of problem solving in a specific domain. From this perspective, the agenda for the knowledge acquisition research community includes developing tools and methods to aid experts in their efforts to express, elaborate, and improve their models of the domain. This functional view of expertise helps account for several problems that typically arise in practical knowledge acquisition projects, many of which stem directly from the inadequacies of representations used at various stages of system development. to counter these problems, we emphasize the use of mediating representations as a means of communication between expert and knowledge engineer, and intermediate representations to help bridge the gap between the mediating representations themselves, as well as between the mediating representations and a particular implementation formalism. © 1993 John Wiley & Sons, Inc.     

Knowledge work support by semantic task management

This paper describes the particular requirements of knowledge work in an industrial setting and its support by semantic technologies. This setting is characterized by specific demands with respect to information handling, communication and work coordination. It is shown how semantic technologies can meet these demands. Specifically, the Social Semantic Desktop (SSD) is discussed that covers requirements for individual structuring and proceeding as well as organizational needs. It is discussed which aspects come to the fore in an industrial setting and require particular consideration. Here we find a focus on communication and on work coordination. The latter is addressed by semantic task management and allows for new approaches towards experience management in industry. In this respect the SSD opens up completely new opportunities. It is shown how such a framework has been realized in the European Integrated Project Nepomuk.     

Knowledge types: a practical approach to guide knowledge engineering in domains of building design

Abstract: This paper presents experiences and findings achieved through several expert system projects in domains of technical buiding design. The main focus is on knowledge acquisition and knowledge decomposition. Different approaches are presented and discussed. Four types of knowledge are presented: object knowledge, performance knowledge, event knowledge and metaknowledge, and the applicability of this classification to building design is justified. The paper includes a listing of experiences gained by real world testing of an expert system, and finally we outline guidelines to knowledge engineering in the domain of technical building     

Expert knowledge acquisition and the unwilling expert: a knowledge engineering perspective

Expert systems are an evolving technology with the potential to make human expertise widely and cheaply available. The literature describing the development of expert systems generally assumes that experts willingly give up their knowledge. This is unrealistic and may be a reason why most expert system projects fail. This paper explores the problem of unwilling experts from the perspective of a knowledge engineer building an expert system. The link between knowledge and organizational power is established and human motivation theories are discussed. Finally, a new motivational approach is introduced to help the knowledge engineer deal with unwilling experts.     

A tourism destination recommender system using users’ sentiment and temporal dynamics

With the development and popularity of social networks, an increasing number of consumers prefer to order tourism products online, and like to share their experiences on social networks. Searching for tourism destinations online is a difficult task on account of its more restrictive factors. Recommender system can help these users to dispose information overload. However, such a system is affected by the issue of low recommendation accuracy and the cold-start problem. In this paper, we propose a tourism destination recommender system that employs opinion-mining technology to refine user sentiment, and make use of temporal dynamics to represent user preference and destination popularity drifting over time. These elements are then fused with the SVD+ + method by combining user sentiment and temporal influence. Compared with several well-known recommendation approaches, our method achieves improved recommendation accuracy and quality. A series of experimental evaluations, using a publicly available dataset, demonstrates that the proposed recommender system outperforms the existing recommender systems.