decision support system example of a decision support system for john day reservoir recommender systems concepts collective intelligence relevance star ratings long tail methods and challenges cold start collaborative filtering dimensionality reduction implicit data collection itemitem collaborative filtering matrix factorization preference elicitation similarity search social loafing implementations collaborative search engine content discovery platform decision support system music genome project product finder research grouplens research movielens netflix prize vte a decision support system dss is an information system that supports business or organizational decisionmaking activities dsss serve the management operations and planning levels of an organization usually mid and higher management and help people make decisions about problems that may be rapidly changing and not easily specified in advanceie unstructured and semistructured decision problems decision support systems can be either fully computerized or humanpowered or a combination of both while academics have perceived dss as a tool to support decision making process dss users see dss as a tool to facilitate organizational processes defines a properly termed dss as follows dss tends to be aimed at the less well structured underspecified problem that upper level managers typically face dss attempts to combine the use of models or analytic techniques with traditional data access and retrieval functions dss specifically focuses on features which make them easy to use by noncomputerproficient people in an interactive mode and dss emphasizes flexibility and adaptability to accommodate changes in the environment and the decision making approach of the user dsss include knowledgebased systems a properly designed dss is an interactive softwarebased system intended to help decision makers compile useful information from a combination of raw data documents and personal knowledge or business models to identify and solve problems and make decisions typical information that a decision support application might gather and present includes inventories of information assets including legacy and relational data sources cubes data warehouses and data marts comparative sales figures between one period and the next projected revenue figures based on product sales assumptions history the concept of decision support has evolved mainly from the theoretical studies of organizational decision making done at the carnegie institute of technology during the late 1950s and early 1960s and the implementation work done in the 1960s dss became an area of research of its own in the middle of the 1970s before gaining in intensity during the 1980s in the middle and late 1980s executive information systems eis group decision support systems gdss and organizational decision support systems odss evolved from the single user and modeloriented dss according to sol 1987 in 1987 texas instruments completed development of the gate assignment display system gads for united airlines this decision support system is credited with significantly reducing travel delays by aiding the management of ground operations at various airports beginning with ohare international airport in chicago and stapleton airport in denver colorado beginning in about 1990 data warehousing and online analytical processing olap began broadening the realm of dss as the turn of the millennium approached new webbased analytical applications were introduced the advent of more and better reporting technologies has seen dss start to emerge as a critical component of management design examples of this can be seen in the intense amount of discussion of dss in the education environment dss also have a weak connection to the user interface paradigm of hypertext both the university of vermont promis system for medical decision making and the carnegie mellon zogkms system for military and business decision making were decision support systems which also were major breakthroughs in user interface research furthermore although hypertext researchers have generally been concerned with information overload certain researchers notably douglas engelbart have been focused on decision makers in particular taxonomies using the relationship with the user as the criterion haettenschwiler differentiates passive active and cooperative dss a passive dss is a system that aids the process of decision making but that cannot bring out explicit decision suggestions or solutions an active dss can bring out such decision suggestions or solutions a cooperative dss allows for an iterative process between human and system towards the achievement of a consolidated solution the decision maker or its advisor can modify complete or refine the decision suggestions provided by the system before sending them back to the system for validation and likewise the system again improves completes and refines the suggestions of the decision maker and sends them back to them for validation another taxonomy for dss according to the mode of assistance has been created by daniel power he differentiates communicationdriven dss datadriven dss documentdriven dss knowledgedriven dss and modeldriven dss a communicationdriven dss enables cooperation supporting more than one person working on a shared task examples include integrated tools like google docs or microsoft groove a datadriven dss or dataoriented dss emphasizes access to and manipulation of a time series of internal company data and sometimes external data a documentdriven dss manages retrieves and manipulates unstructured information in a variety of electronic formats a knowledgedriven dss provides specialized problemsolving expertise stored as facts rules procedures or in similar structures a modeldriven dss emphasizes access to and manipulation of a statistical financial optimization or simulation model modeldriven dss use data and parameters provided by users to assist decision makers in analyzing a situation they are not necessarily dataintensive dicodess is an example of an open source modeldriven dss generator using scope as the criterion power differentiates enterprisewide dss and desktop dss an enterprisewide dss is linked to large data warehouses and serves many managers in the company a desktop singleuser dss is a small system that runs on an individual managers pc components design of a drought mitigation decision support system three fundamental components of a dss architecture are the database or knowledge base the model ie the decision context and user criteria the user interface the users themselves are also important components of the architecture development frameworks similarly to other systems dss systems require a structured approach such a framework includes people technology and the development approach the early framework of decision support system consists of four phases intelligence searching for conditions that call for decision design developing and analyzing possible alternative actions of solution choice selecting a course of action among those implementation adopting the selected course of action in decision situation dss technology levels of hardware and software may include the actual application that will be used by the user this is the part of the application that allows the decision maker to make decisions in a particular problem area the user can act upon that particular problem generator contains hardwaresoftware environment that allows people to easily develop specific dss applications this level makes use of case tools or systems such as crystal analytica and ithink tools include lower level hardwaresoftware dss generators including special languages function libraries and linking modules an iterative developmental approach allows for the dss to be changed and redesigned at various intervals once the system is designed it will need to be tested and revised where necessary for the desired outcome classification there are several ways to classify dss applications not every dss fits neatly into one of the categories but may be a mix of two or more architectures holsapple and whinston the support given by dss can be separated into three distinct interrelated categories personal support group support and organizational support dss components may be classified as inputs factors numbers and characteristics to analyze user knowledge and expertise inputs requiring manual analysis by the user outputs transformed data from which dss decisions are generated decisions results generated by the dss based on user criteria dsss which perform selected cognitive decisionmaking functions and are based on artificial intelligence or intelligent agents technologies are called intelligent decision support systems idss the nascent field of decision engineering treats the decision itself as an engineered object and applies engineering principles such as design and quality assurance to an explicit representation of the elements that make up a decision applications dss can theoretically be built in any knowledge domain one example is the clinical decision support system for medical diagnosis there are four stages in the evolution of clinical decision support system cdss the primitive version is standalone and does not support integration the second generation supports integration with other medical systems the third is standardbased and the fourth is service modelbased dss is extensively used in business and management executive dashboard and other business performance software allow faster decision making identification of negative trends and better allocation of business resources due to dss all the information from any organization is represented in the form of charts graphs ie in a summarized way which helps the management to take strategic decision for example one of the dss applications is the management and development of complex antiterrorism systems other examples include a bank loan officer verifying the credit of a loan applicant or an engineering firm that has bids on several projects and wants to know if they can be competitive with their costs a growing area of dss application concepts principles and techniques is in agricultural production marketing for sustainable development for example the dssat4 package dss are also prevalent in forest management where the long planning horizon and the spatial dimension of planning problems demands specific requirements all aspects of forest management from log transportation harvest scheduling to sustainability and ecosystem protection have been addressed by modern dsss in this context the consideration of single or multiple management objectives related to the provision of goods and services that traded or nontraded and often subject to resource constraints and decision problems the community of practice of forest management decision support systems provides a large repository on knowledge about the construction and use of forest decision support systems a specific example concerns the canadian national railway system which tests its equipment on a regular basis using a decision support system a problem faced by any railroad is wornout or defective rails which can result in hundreds of derailments per year under a dss the canadian national railway system managed to decrease the incidence of derailments at the same time other companies were experiencing an increase wikimedia commons has media related to decision support systems argument map cognitive assets organizational decision theory enterprise decision management expert system judgeadvisor system land allocation decision support system list of concept and mindmapping software morphological analysis problemsolving online deliberation participation decision making predictive analytics project management software self service software spatial decision support system strategic planning software marius cioca florin filip 2015 decision support systems a 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