User:Gwileyb/sandbox

Approaches to Concept Search[edit]

In general, information retrieval research and technology can be divided into two broad categories: semantic and statistical. Information retrieval systems that fall into the semantic category will attempt to implement some degree of syntactic and semantic analysis of the natural language text that a human user would provide (also see computational linguistics). Systems that fall into the statistical category will find results based on statistical measures of how closely they match the query. However, systems in the semantic category also often rely on statistical methods to help them find and retrieve information.[3]Another approach makes use of concept maps, mind maps or concept hierarchies based on domain knowledge to replace fine grained contextual queries. Efforts to provide information retrieval systems with semantic processing capabilities have basically used four (was three) different approaches: Auxiliary structures Local co-occurrence statistics Transform techniques (particularly matrix decompositions) Concept Maps

<! --- after Transform Techniques add >

Concept Maps
Concept Maps are a well known method for describing knowledge domains. A Concept Search using concept maps requires that a user select a domain of knowledge using a few specific words and then selects concepts presented from a search based on the concept map presented by the IR Concept Map system. The advantage of this approach is to replace the human deep understanding of the domain and requirement for very fine grained search query with automation that guides the user through the knowledge domain. The results can be as specific as pieces of information (Declarative sentences, formulae, and digital media) from the document source which can be combined with knowledge of the relationship of the information to the domain as a whole. The Concept Map approach is very similar to topic maps with automation to identify the parts of text that are specifically about a concept not matched to a human query.