
Knowledge discovery
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Information retrieval
Information retrieval is the activity of obtaining information resources relevant to an information need from a collection of information resources. Searches can be based on metadata or on full-text (or other content-based) indexing. 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 . [ edit ] HistoryData mining (the analysis step of the "Knowledge Discovery in Databases" process, or KDD), [ 1 ] an interdisciplinary subfield of computer science , [ 2 ] [ 3 ] [ 4 ] is the computational process of discovering patterns in 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 information from a data set and transform it into an understandable structure for further use. [ 2 ] Aside from the raw analysis step, it involves database and data management aspects, data preprocessing , model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization , and online updating . [ 2 ]
Data mining
Data warehouse
Knowledge extraction
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 . [ edit ] Overview

