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4/10: Managing Knowledge & IS Tools for Decision-Making • Knowledge Management – Office & document management systems – Knowledge work systems – Group collaboration systems, intranet knowledge environments – Artificial intelligence: Expert Systems, Case-based reasoning – Neural networks, Fuzzy logic, Genetic algorithms, Hybrid AI systems, Intelligent agents • Enhancing Management Decision-Making – Decision Support Systems (DSS) – Group DSS – Executive Support Systems (ESS) Knowledge Management • “ The process of systematically and actively managing and leveraging the stores of knowledge in an organization.” • An organization’s knowledge base may include: – Structured internal knowledge – External knowledge – Informal internal knowledge (tacit knowledge) Information Work • “Work that primarily consists of creating or processing information.” • Two types of workers: – Data workers: those who process & disseminate information & paperwork. – Knowledge workers: those who create knowledge; those who design products & services. Office & Document Management Systems • 3 basic functions of an office: – Managing & coordinating the work of data & knowledge workers – Connecting the work of the local info workers with the larger organization – Connecting the organization to the external environment Office Workers: Activities • Managing documents – Document creation, storage, retrieval, dissemination • Scheduling for individuals & groups • Communicating for individuals & groups – Voice,digital, & document-based communications • Managing data Office Systems Help Office Workers • “Computer systems, such as word processing, voice mail, and imaging that are designed to increase productivity of office workers.” • Help with: – – – – Document creation, dissemination, & retrieval Collaboration Scheduling Etc. Document Imaging Systems • Convert printed documents & images to digital form for storage & access by computer. • Not-often-used documents can be stored on a jukebox (optical disk system w/ multiple disks). • Alternative to DIS: Intranets – Workers publish documents to web-based form directly Knowledge Work Systems • “Information systems that aid knowledge workers in the creation and integration of new knowledge in the organization.” • 3 key roles for knowledge workers: – Keeping the organization up to date with knowledge in external world – Serving as internal consultants in their areas of expertise – Acting as change agents to evaluate, initialize, & promote change. Requirements for KWS • Specialized tools needed for particular task • User-friendly interface • Access to external databases • Examples of KWS: – CAD – Virtual reality systems, VRML systems – Investment workstations CAD: Computer-Aided Design • Automates creation & modification of designs by using computers. Virtual Reality, VRML Systems • Have visualization, rendering, and simulation capabilities beyond conventional CAD. • VRML: Virtual Reality Markup Language – Virtual reality designed for the Web Group Collaboration Systems • Groupware – “Software that provides functions and services that support the collaborative activities of workgroups.” – Examples: • • • • publishing: tracking multiple users’ edits to a document replication: keeping identical data on multiple PCs discussion tracking security: preventing unauthorized access to data Group Collaboration Systems • Intranet knowledge environments – An alternative to traditional groupware – Cheaper, easier to maintain for email, discussion groups, multimedia Web documents • Which to choose? – Groupware: projects requiring extensive coordination & management, editing on the fly, tracking revisions, greater security – Intranet: simple tasks like sharing documents, email, publishing documents, etc. Artificial Intelligence • “The effort to develop computer-based systems that behave like humans.” (inc. hardware & software) • AI systems are based on human expertise, knowledge, and selected reasoning patterns, but do not exhibit human intelligence. • Why would businesses want this science-fiction idea? – – – – – to preserve expertise that may be lost to store information in an active form to create a mechanism invulnerable to human feelings to eliminate boring & unsatisfying jobs to enhance an organization’s knowledge base by providing interactivity. Expert Systems • “Knowledge-intensive computer program that captures the expertise of a human in limited domains of knowledge.” • Narrow & brittle • Perform tasks that a professional could do in a few minutes or hours. Expert Systems: Parts • Knowledge base: model of human knowledge used by ES. • Rule base: the part of the knowledge base that is contained in IF/THEN structures. • Knowledge frames: organizes knowledge into chunks of interrelated characteristics. • AI shell: programming environment of an ES. • Knowledge engineer: a systems analyst expert in converting human knowledge into an ES. Case-based reasoning • “Artificial intelligence technology that represents knowledge as a database of cases and solutions.” • Each new case is compared with existing cases to suggest a solution. Each new case is added to the database of cases upon arriving at a satisfactory solution. Other Intelligent Techniques • Neural networks – attempt to emulate the processing patterns of the biological brain; have a general capacity to learn. • Fuzzy logic – rule-based AI that tolerates imprecision using membership functions. • Genetic algorithms – Solution evolves through mutation, adaptation, and natural selection out of possible answers. Intelligent agents • “Software that uses a built-in or learned knowledge base to carry out specific, repetitive, and predictible tasks for the user, business process, or other software application.” • Example uses: – – – – wizards in MS Office delete junk email find cheapest airfare search auctions for lowest price on item • Bots – http://www.mySimon.com Enhancing Management DecisionMaking • Decision Support Systems (DSS) – “Computer systems for management that combines data, analytical tools, and models to support semistructured and unstructured decision-making. – MIS are predefined management reports, etc., not unstructured. Two types of DSS • Model-driven DSS – “Primarily stand-alone system that uses a model to perform “what-if” analysis.” • Data-driven DSS – “A system that allows users to extract & analyze information in large databases.” Data-driven DSS: Datamining • Associations: things linked to a single event. • Sequences: events linked over time. • Classification: patterns that describe a group, inferring a set of rules. • Clustering: like classification, but no defined group yet exists. • Forecasting: using a series of values to forecast what other values may be. Parts of a DSS • Database: all the data – historical and/or current from various applications. • Software system – Software tools used for analysis. • Examples inc. web-based DSS Examples of DSS • • • • American Airlines: price & route selection Frito-Lay: price, advertising, & promotion mix Texas Oil & Gas: evaluation of drilling sites General Accident Insurance: fraud detection Group DSS • “An interactive computer-based system that facilitates solutions to unstructured problems by decision-makers working as a group.” • Parts: – Hardware: conference facility itself, PCs, overheads, etc. – Software tools: electronic questionnaires, brainstorming tools, voting tools, etc. – People Executive Support Systems (ESS) • “Information systems for strategic-level unstructured decision-making in an organization through advanced graphics & communications.” • Drilling down: ability to move from summary data to lower and lower levels of detail. Benefits of ESS • Easy to use; little training needed. • Ability to analyze, compare, and highlight trends. • Enhance quality of decision-making because of drill-down capability