Knowledge discovery

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http://en.wikipedia.org/wiki/Information_retrieval

Information retrieval - Wikipedia, the free encyclopedia

Information retrieval ( IR ) is the area of study concerned with searching for documents, for information within documents, and for metadata about documents, as well as that of searching structured storage , relational databases , and the World Wide Web . There is overlap in the usage of the terms data retrieval, document retrieval , information retrieval, and text retrieval , but each also has its own body of literature, theory, praxis , and technologies. IR is interdisciplinary , based on computer science , mathematics , library science , information science , information architecture , cognitive psychology , linguistics , statistics and law . Automated information retrieval systems are used to reduce what has been called " information overload ". Many universities and public libraries use IR systems to provide access to books, journals and other documents. Web search engines are the most visible IR applications .
Data mining (the analysis step of the knowledge discovery in databases process, [ 1 ] or KDD), a relatively young and interdisciplinary field of computer science [ 2 ] [ 3 ] is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence , machine learning , statistics and database systems . [ 2 ] The overall goal of the data mining process is to extract knowledge from a data set in a human-understandable structure [ 2 ] and besides the raw analysis step involves database and data management aspects, data preprocessing , model and inference considerations, interestingness metrics, complexity considerations, post-processing of found structure, visualization and online updating . [ 2 ]

Data mining - Wikipedia, the free encyclopedia

http://en.wikipedia.org/wiki/Data_mining
http://en.wikipedia.org/wiki/Data_warehouse In computing , a data warehouse ( DW ) is a database used for reporting and analysis. The data stored in the warehouse are uploaded from the operational systems (such as market place,sales etc. as shown in fig). The data may pass through an operational data store for additional operations before they are used in the DW for reporting. The typical ETL-based data warehouse uses staging, integration, and access layers to house its key functions. The staging layer or staging database stores raw data extracted from each of the disparate source data systems.

Data warehouse - Wikipedia, the free encyclopedia

Knowledge extraction - Wikipedia, the free encyclopedia

http://en.wikipedia.org/wiki/Knowledge_extraction Knowledge Extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to Information Extraction ( NLP ) and ETL ( Data Warehouse ), the main criteria is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge (reusing identifiers or ontologies) or the generation of a schema based on the source data. The RDB2RDF W3C group [ 1 ] is currently standardizing a language for extraction of RDF from relational databases.
Knowledge Retrieval seeks to return information in a structured form, consistent with human cognitive processes as opposed to simple lists of data items. It draws on a range of fields including epistemology (theory of knowledge), cognitive psychology , cognitive neuroscience , logic and inference , machine learning and knowledge discovery , linguistics , and information technology . The goal of knowledge retrieval systems is to reduce the burden of those processes by improved search and representation. http://en.wikipedia.org/wiki/Knowledge_retrieval

Knowledge retrieval - Wikipedia, the free encyclopedia

Knowledge discovery - Wikipedia, the free encyclopedia

From Wikipedia, the free encyclopedia Knowledge discovery is a concept of the field of computer science that describes the process of automatically searching large volumes of data for patterns that can be considered knowledge about the data [ 1 ] . It is often described as deriving knowledge from the input data . This complex topic can be categorized according to 1) what kind of data is searched; and 2) in what form is the result of the search represented. http://en.wikipedia.org/wiki/Knowledge_discovery