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Topic: Knowledge discovery

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	Bulletin Dec/Jan 2000: AM99, Track 1
		The focus on knowledge discovery is timely: it is the theme of the November 1999 issue of Communications of the ACM, and the Summer 1999 issue of Library Trends (edited by ASIS members Jian Qin and M. Jay Norton) deals specifically with knowledge discovery in bibliographic databases.
		Because terms such as data, information and knowledge are not used consistently, it is important to look beyond the terms and determine what is actually being analyzed and synthesized by the various techniques described briefly in the remainder of this article.
		Information should not build up a dead structure: the body of knowledge is in continuous evolution and it is vital, in order to forecast and influence the future, that information should contain at least the seeds of tomorrow's progress and discoveries.
	www.asis.org /Bulletin/Jan-00/track_1.html (1280 words)

	Knowledge discovery from GIS in 'Natural Resources Targeting'
		This activity of knowledge discovery requires a thorough analysis for extraction of implicit knowledge, spatial relations, patterns and nugget effect in spatial datasets.
		General process of knowledge discovery is the extraction of spatial association, discrimination, deviations/evolution rules describing temporal changes of a prominent cluster.
		Knowledge driven approaches are usually a forward-chaining expert system in which the method of propagation of favourability measure through the inference network may include the Bayesian updating, fuzzy-logic or belief function for computation of posterior values of favourability given evidence(s).
	www.gisdevelopment.net /application/nrm/overview/mi01niharpf.htm (2735 words)

	Knowledge Discovery
		Knowledge discovery is not industry biased, though it is more prominent in mid- to large-size companies.
		In order to simplify the process of knowledge discovery, also known as data mining, let's look at the fictitious, information-rich company known as Local Grocer that has decided to implement the practice of predictive modeling.
		Knowledge discovery worked well in this instance, though the process is equally as effective in industries such as telecommunications, hospitality and retail.
	www.the-modeling-agency.com /knowledge-discovery.html (358 words)

	Software Magazine - Eureka! Knowledge Discovery
		Knowledge discovery and data mining (KDD) is evolving from an esoteric art and a point solution, to a mainstream technology embedded in a variety of solutions, to help businesses turn information into insight.
		Knowledge discovery and data mining (KDD) is a relatively new discipline gaining visibility due to the exponential growth in data collection.
		Knowledge discovery is quickly moving from gear-head status to greater and more general acceptance within the IT and business communities.
	www.softwaremag.com /L.cfm?doc=archive/2000dec/KnowledgeDiscovery.html (2639 words)

	'Knowledge discovery' could speed creation of new products
		They are developing a method to extract knowledge from data, promising to speed up the process of discovery in many areas of research, including work aimed at creating new drugs, fuel additives, catalysts and rubber compounds.
		The method, called "discovery informatics," enables researchers to test new theories on the fly and literally see how well their concepts might work in real time via a three-dimensional display, said Venkat Venkatasubramanian, another professor of chemical engineering working to develop the new system.
		Discovery informatics depends on a two-part repeating cycle made up of a "forward model" and an "inverse process" and two types of artificial intelligence software: hybrid neural networks and genetic algorithms.
	news.uns.purdue.edu /UNS/html4ever/2004/041018.Caruthers.discover.html (2221 words)

	Knowledge Discovery
		Bibliography: Data Mining and Knowledge Discovery in Databases - A bibliography of KDD research from a Computer Science perspective.
		Knowledge Discovery In Databases: Tools and Techniques - Article by Peggy Wright that presents the results of a literature survey outlining the state-of-the-art in KDD techniques and tools.
		The primary role of this repository is to serve as a benchmark testbed to enable researchers in knowledge discovery and data mining to scale existing and future data analysis algorithms to very large and complex data sets.
	supercrawler.com /Reference/Knowledge_Management/Knowledge_Discovery (648 words)

	The Lotus Knowledge Discovery System: Tools and experiences
		Based on its experience and on the existing large body of knowledge management literature, the team decided that knowledge management software should provide virtual “places” where users can organize information, services, and tools to support their particular needs, while at the same time maintaining and updating information in a more general context.
		Information discovery is a way to provide access to all the information that is relevant in a corporate environment without prior knowledge of its existence.
		While the Knowledge Discovery System was being developed, Lotus worked with a small set of design partners who tested early versions of the software in real-life environments to solve real organizational problems.
	www.research.ibm.com /journal/sj/404/pohs.html (4151 words)

	BrainDex the knowledge source - Free Online Encyclopedia - Discovery (observation) (Site not responding. Last check: 2007-10-11)
		A discovery is a novel observation, usually of a natural phenomenon.
		The discovery that the Earth was not flat
		Experiments by JJ Thomson in 1897 led to the discovery of a fundamental building block of matter - electron.
	www.braindex.com /encyclopedia/index.php/Discovery_(observation) (137 words)

	Knowledge Discovery In Databases (Site not responding. Last check: 2007-10-11)
		Knowledge Discovery In Databases (KDD) is a process an organization can use to tap into the hidden knowledge contained within the large volume of data an organization collects.
		The improvement comes from analyzing and documenting what forms of knowledge are gained given a stated knowledge requirement and implementing each of the phases of KDD - data selection, cleaning, enrichment and data mining.
		Shallow knowledge can be easily extracted with query tools and it's estimated that shallow knowledge accounts for 80% of the knowledge in an organization's data.
	www.chips.navy.mil /archives/00_oct/database.html (1622 words)

	Context Mediation among Knowledge Discovery Components:
		Knowledge Discovery is concerned with the extraction of actionable information from large databases.
		Contextual domain knowledge mediation deals with the integration of pre-existing knowledge about data, preferences and biases ubiquitous in multiple contexts, which are incorporated in the knowledge discovery process.
		Contextual knowledge pattern mediation is concerned with the interpretation of the outputs from data mining algorithms from different perspectives.
	www.dissertation.com /book.php?method=ISBN&book=1581122284 (524 words)

	Knowledge Discovery Associates (Site not responding. Last check: 2007-10-11)
		Rather than replace current database technology, we extend its typical query-and-response approach to one which incorporates knowledge of the enterprise, its purposes, processes, and problems, opening the door to the discovery of valuable new business knowledge in existing data.
		Knowledge Discovery Associates is a consulting practice based in the Boston area, serving clients nationwide.
		It is an affiliation of world-class data analysts and expert system implementers, who are experienced in applying knowledge discovery, data mining, and intelligent data analysis to business data in a variety of settings.
	www.knowledge-discovery.com (160 words)

	ECML/PKDD-2004 Knowledge Discovery and Ontologies Workshop
		The workshop is concerned with the interaction between prior knowledge as encoded in ontologies and derived knowledge as obtained by a knowledge discovery process.
		Currently, in most KDD projects, prior knowledge is only present implicitly (in the head of the human analyst) or in the form of textual documentation.
		Somewhat less traditional is the role of ontologies in incremental approaches to knowledge discovery, in which ontologies and machine learning methods are used in combination to mine, interpret and (re-)organise knowledge.
	olp.dfki.de /pkdd04/cfp.htm (995 words)

	InformationWeek.com
		The Discovery Server has a three-tier architecture: Discovery Server clients, which include the taxonomy editor and the client applications; Discovery Server application server objects, which comprise spiders, clustering, and client objects; and the IBM DB2-based Discovery Server database.
		A big part of the Knowledge Discovery System's as-yet-unrealized promise will be its ability to mine the information stored in customer-relationship management, enterprise resource planning, material-requirements planning, and other types of business applications.
		Lotus Discovery System combines the last two components, knowledge discovery and expertise location (with privacy control), while providing a viewing and organizing mechanism in the form of the K-station portal application.
	www.informationweek.com /824/lotus.htm (889 words)

	Amazon.com: Knowledge Discovery in Databases: Books: Gregory Piatetsky-Shapiro,William J. Frawley (Site not responding. Last check: 2007-10-11)
		Knowledge Discovery in Databases brings together current research on the exciting problem of discovering useful and interesting knowledge in databases.
		The task of uncovering these secrets is called "discovery in databases." This loosely defined subfield of machine learning is concerned with discovery from large amounts of possible uncertain data.
		Following an overview of knowledge discovery in databases, thirty technical chapters are grouped in seven parts which cover discovery of quantitative laws, discovery of qualitative laws, using knowledge in discovery, data summarization, domain?specific discovery methods, integrated and multi-paradigm systems, and methodology and application issues.
	www.amazon.com /exec/obidos/tg/detail/-/0262660709?v=glance (625 words)

	NASA IS/IDU/Knowledge Discovery (Site not responding. Last check: 2007-10-11)
		The IDU Knowledge Discovery (KD) technical area -- or, more properly, Knowledge Discovery for Understanding and Analysis -- develops interactive methods for discovering classification rules and inferring causation, starting from background knowledge and observed associations.
		Knowledge discovery is the non-trivial process of finding valid, potentially useful, and ultimately understandable patterns.
		Knowledge discovery is often a mixed-initiative process, guided by domain-specific knowledge.
	is.arc.nasa.gov /IDU/KD.html (421 words)

	"Knowledge Discovery" Could Speed Creation Of New Products
		A team at Purdue University currently is developing a similar "data-rich" environment for scientific discovery that uses high-performance computing and artificial intelligence software to display information and interact with researchers in the language of their specific disciplines.
		"Most current approaches to computer-aided discovery center on mining data in a process that assumes there is a nugget of gold that needs to be found in a sea of irrelevant information," Caruthers said.
		Discovery informatics, which has numerous potential applications, is that modeling superhighway.
	www.spacedaily.com /news/internet-04zzzv.html (1899 words)

	KDD'99 Knowledge Discovery Contest Results (Site not responding. Last check: 2007-10-11)
		The purpose of the knowledge discovery contest held in conjunction with the KDD'99 conference was to showcase methods for discovering higher-level knowledge from data.
		Participants were asked to apply a range of knowledge discovery techniques to the same data used in the 1998 competition.
		"Knowledge Discovery in a Charitable Organization's Donor Database" by Saharon Rosset and Aron Inger of Amdocs (Israel) Ltd.
	www-cse.ucsd.edu /users/elkan/kdresults.html (183 words)

	knowledge Discovery
		By introducing an interceptive coordinator, a directive coordinator, a knowledge synthesizer, a knowledge deductor and a knowledge inductor, we have obtained a knowledge discovery system that is time-space variant.
		An old (existing) knowledge base is used to create a new knowledge base, which is then synthesized with a basic knowledge base to produce a extended knowledge base.
		In most cases, there are a large amount of unrelated rules (or independent nodes if represented as a decision tree) in a knowledge base, and it is desirable to discover additional knowledge from the given knowledge base, by finding out if some of them are related (connected if decision tree).
	www.zaptron.com /knowledge (701 words)

	Amazon.com: Geographic Data Mining & Knowledge Discovery: Books: Harvey J. Miller,Jiawei Han (Site not responding. Last check: 2007-10-11)
		Geographic Data Mining and Knowledge Discovery is the interrogation of large databases using efficient computational methods.
		Developed out of contributions to the highly-respected Varenius Project in 1999, this collection addresses the special challenges to be found in knowledge discovery and data mining from geographic databases.
		Knowledge Discovery in Databases: PKDD 2003 : 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Cavtat-Dubrovnik,...
	www.amazon.com /exec/obidos/tg/detail/-/0415233690?v=glance (819 words)

	Data Mining and Knowledge Discovery journal
		Data Mining and Knowledge Discovery is a peer reviewed journal publishing articles on all aspects of Knowledge Discovery in Databases (KDD) and data mining methods for extracting high-level representations (patterns and models) from data.
		The growing importance and success of Data Mining and Knowledge Discovery in Databases (KDD), has led us to form a new technical journal to document research advances by this rapidly growing community.
		The second International Conference on Knowledge Discovery and Data Mining (KDD-96) held in Portland, OR, USA, attracted over 500 attendees and continued on the success of the first conference, KDD-95.
	www.research.microsoft.com /research/datamine/jdmkdinfo.htm (513 words)

	Knowledge discovery, data mining knowledge discovery, knowledge discovery and data mining (Site not responding. Last check: 2007-10-11)
		Knowledge discoveryIDM Workshop Template, data mining knowledge discovery, knowledge discovery and data mining..
		Knowledge discovery in text (KDT), sometimes referred to as text mining, is a fast-developing field that encompasses a variety of methodologies,.
		This is the homepage of the Datamining and Knowledge Discovery Journal knowledge discovery..
	www.watchcomputer.com /knowledge-discovery.html (326 words)

	Dataminig & Knowledge Discovery
		The knowledge discovery mine contains a lot of useful links to other resources, a list of relevant kdd publications, a catalog of kdd tools and a list of Siftware - tools for knowledge discovery and datamining.
		This is the homepage of the Datamining and Knowledge Discovery Journal.
		If you are searching for a good book on data mining and knowledge discovery - here it is! This link gives you an overview of topics covered by the book.
	www.rvs.uni-bielefeld.de /~heiko/knowledge.html (350 words)

	Omniseek: /Directory /Knowledge Management /Knowledge Discovery /Data Mining /
		The continuing rapid growth of on-line data and the widespread use of databases necessitate the development of techniques for extracting useful knowledge and for facilitating database access.
		The primary role of this repository is to serve as a benchmark testbed to enable researchers in knowledge discovery and data min
		Data mining (or knowledge discovery in databases), is a new research area developing methods and systems for extracting interesting and useful information from large sets of data.
	www.omniseek.com /srch/{39162} (423 words)

	Knowledge Discovery in Databases and Data Mining
		Spatial Clustering Methods in Data Mining: A Survey '', in H. Miller and J. Han (eds.), Geographic Data Mining and Knowledge Discovery, Taylor and Francis, 2001.
		Discovery of Multiple-Level Association Rules from Large Databases (PDF)'', IEEE Transactions on Knowledge and Data Engineering, 11(5), 1999.
		Mining Knowledge in Geographical Data'', accepted by IEEE Comuter, 1998.
	www-sal.cs.uiuc.edu /~hanj/pubs/kdd.htm (2880 words)

	Distributed Knowledge Networks
		The acquired knowledge, in addition to being of immediate value to the users, would also be used by software agents to hypothesize likely events based on information available and then seek out additional data to support or refute the hypothesis (e.g., in the context of data-driven scientific discovery).
		Thus it is desirable to use mobile software agents that transport themselves to the data repositories, or stationary software agents that reside at the repositories, to perform as much analysis as possible where the data are located, and return only the results of analysis in order to conserve network bandwidth.
		Design of knowledge representations that lend themselves to incremental update of knowledge structures using only the new data and the design of efficient update algorithms; The algorithm that we have designed for incremental induction of support vector machines provides an example of this approach.
	www.cs.iastate.edu /~honavar/ailab/projects/inclearn.html (802 words)

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