O'Leary, D.E. (1998) "Enterprise knowledge management," IEEE Computer, 1998, 31 (3) pp. 54-- 61.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....management has been introduced into the CSCW field (c.f. Greif 1998) It seem to have much in common with organisational memory, but an emphasis on managing large repositories of information with information retrieval and artificial intelligence techniques can be noted (see Abecker et al. 1998; O Leary 1998). One of the first organisational memory systems described in the literature was gIBIS (Conklin and Begeman 1988) The aim of gIBIS was to make decision processes explicit by capturing the argumentation. 1 Another system is TeamBuilder , of which the objectives is to support team members in ....

O'Leary, D.E. (1998) "Enterprise knowledge management," IEEE Computer, 1998, 31 (3) pp. 54-- 61.

....has been introduced into the CSCW field (cf. Greif 1998) It seems to have much in common with organisational memory. However, an emphasis on managing large repositories of information with information retrieval and artificial intelligence techniques can be noted (see, Abecker et al. 1998; O Leary 1998). One of the first organisational memory systems described in the literature was gIBIS (Conklin and Begeman 1988) The aim of gIBIS was to make decision processes explicit by capturing the argumentation. 1 Another system is TeamBuilder, of which the objectives is to support team members in ....

O'Leary, D.E. (1998) "Enterprise knowledge management," IEEE Computer, 1998, 31 (3) pp. 54-- 61.

....enterprise ontology guided search in XML documents that may consitute a part of a corporate memory. Keywords: XML, World Wide Web, knowledge management, document based corporate memory, enterprise ontology, information retrieval. 1 Introduction Extending the definitions proposed by [28] [20], we consider a corporate memory as an explicit, disembodied, persistent representation of knowledge and information in an organization, in order to facilitate its access and reuse by members of the organization, for their tasks. We consider its building as relying on the following steps [11] 1) ....

.... models, user models) could help to filter the information to be retrieved Are inference capabilities needed in this purpose For information search on the Web, in addition to traditional search engines such as Altavista, other tools were developed: meta engines and intelligent agents [23] 24] [20]. Several types of agents for the Web can be distinguished, according to their functions: search meta tools, functioning by meta index and launching in parallel search on several search engines to compile their results. But if such tools obtain results quickly, they suffer from the ....

D. E. O'Leary. Enterprise Knowledge Management. Computer, 31(3):54-61, March 1998.

....people, organizations, and communities. Knowledge networking or, using a more general term, knowledge management (KM) has attracted significant attention from academic researchers and even executives in Fortune 500 companies [52] 51] Daniel O Leary provides the following definition for KM [33]: Enterprise knowledge management entails formally managing knowledge resources in order to facilitate access and reuse of knowledge, typically by using advanced technology. KM is formal in that knowledge is classified and categorized according to a pre specified but evolving ontology into ....

.... flyer program) is often referred to as data mining or knowledge discovery [37] 28] Generating knowledge algorithmically from multimedia databases (especially text, e.g. customer complaint email, machinery repair reports, brainstorming outputs) is considered the core of knowledge management [33]. Two stages of such a bottom up knowledge management approach are often required: Object Recognition, Segmentation, and Indexing: The most fundamental techniques in IR involve identifying key features in objects. For example, automatic indexing and natural language processing (e.g. noun ....

D. E. O'Leary. Enterprise knowledge management. IEEE Computer, 31(3):54-61, March 1998.

....pieces of information and later, the bringing of it to bear on decision making. Additionally, the management of large repositories of information with information retrieval and artificial intelligence techniques has recently been labelled knowledge management and organisational memory (e.g. see [1, 23, 20]) Within the area of CSCW, several systems have been described. These are often based on hypermedia that link different sources of information. For the most part they have aimed at supporting software development projects or the introspective activities of researchers. An early system of this ....

O'Leary, D.E. (1998) "Enterprise knowledge management," IEEE Computer, 1998, 31 (3) pp. 54--61.

.... (Ashley, 1999) Process embedded textual CBR that actively interjects lessons during decision making meets many KM requirements, including knowledge capture, storage, and reuse; knowledge growth, communication, and preservation, and knowledge gathering, structuring, refinement, and distribution (O Leary, 1998; Decker and Maurer, 1999) Therefore, one of our focal objectives is to identify textual CBR techniques to support case authoring (i.e. identifying, eliciting, representing, and indexing cases) Researchers have investigated using machine learning techniques (Brninghaus and Ashley, 1999) to ....

O'Leary, D. 1998. Enterprise knowledge management. Computer, 31(3): 54-61.

....with the VISTA vision. This environment for software acquisition web management is called SAWMAN. 2 Background The acquisition of major software intensive systems is often problematic. Recent reports from the US General Accounting Office (GAO 1997) and others (e.g. Holland 1998, Nissen, Snider and Lamm 1998) describe a number of problems with the way complex systems are acquired. We in the acquisition research community are at a time when there is substantial opportunity to rethink how the acquisition of software intensive systems should occur to address the recurring problems. At the same time, we ....

D.E. O'Leary. Enterprise Knowledge Management. Computer, 31(3):54-61, 1998.

....search engines like Alta Vista (Shakes et al. 1997) Ahoy actually uses the MetaCrawler parallel web search service and also makes use of two e mail directory services. Heuristic filters are then applied to guess the most likely URL that might be the given person s home page. O Leary (O Leary, 1998) presents examples of a softbot with custom capture in the Price Waterhouse EdgarScan example. In this application, specific EDGAR forms (such as the 10 K, annual report and DEF 14 A, proxy) are parsed to fetch a given industry groups financial statements. Then, a custom Java applet on the client ....

.... more knowledge intensive, more effort is being expended on knowledge management (KM) While much progress has been made on designing IS to support decision making, the art and design of KM systems to preserve, index, formalize and leverage knowledge in organizations is still new (see O Leary (O Leary, 1998) for a review of best practices) Knowledge is fundamentally more complex than information or data, and systems supporting knowledge management have a broader range of design issues. 5.5 Annotate as a Knowledge Management Support System Knowledge management support systems require new design ....

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O'Leary, D. E. (1998). Enterprise knowledge management. IEEE Computer, 31(3):54--61.

....the context of knowledge, and particularly the information system (IS) to help people know (by notifying them) when to look for knowledge to reuse without having to previously formalize it. 1. Introduction Management of knowledge is becoming an increasingly important concern of the enterprise [O Le 98] McC 98] However, current solutions in this area do not seem to be convincing to SME [Die 98] Bart 97] because they do not consider their specific needs [Mah 98 2] Mah 97] Working in close cooperation with KSB Annecy, an SME employing 250 people, we found it necessary to propose a ....

O'Leary Daniel E., Enterprise knowledge Management, Computer, march 98, IIIE, 1998.

.... of project, customer, or project related experiences and know how by establishing best practice or lessons learned databases [37] and, iii) the loss of the middle management information analysis and routing services through new IT solutions like, e.g. intranets, data mining, or data warehouses [25]. Together with the globalization of businesses, an enormous market pressure enforces ever shorter product life cycles. On the other hand, modern information technology allows world wide geographically dispersed development teams, virtual enterprises [32] and close cooperation with suppliers, ....

....with knowledge extracted from texts and from databases. As a first approximation, we propose to have specialized analysis tools and knowledge discovery agents constantly searching the enterprise internal and external web and knowledge sources in order to feed interesting input into the OMIS; see [25] for some examples implemented at Price Waterhouse. Another part are user friendly system interfaces which collect user feedback, comments, and memos in a context sensitive and inobtrusive manner. Although there have been interesting results in document analysis and un derstanding (DAU) since ....

D. O'Leary. Enterprise knowledge management. IEEE Computer, March 1998.

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D. O'Leary, "Enterprise Knowledge Management, " Computer, Vol. 31, No. 3, Mar. 1998, pp. 54--61.

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