Grow up precision recall relationship curve in IR system using GP and fuzzy optimization in optimizing the user query

Title:

Grow up precision recall relationship curve in IR system using GP and fuzzy optimization in optimizing the user query

Creator:

Owasis, Suhail S. J., Snášel, Václav, and Krömer , Pavel

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:b342d732-fd8d-48cc-a5b8-a9b3c11262f5
uuid:b342d732-fd8d-48cc-a5b8-a9b3c11262f5

Subject:

Information retrieval, genetic programming, fuzzy optimization, Boolean operator, term weights, precision, and recall and harmonic mean

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

An information retrieval (IR) system (IRs) (search engine) is said to be efficient, to the degree that always evaluates each object in the information base (database, document base, web,...) like the expert. The ability of IRs's is to retrieve mostly all relevant objects (measured by the recall), and only the (most) relevant objects (measured by the precision) from the collection queried. Recall and precision measures provide the classical measure of the retrieval efficiency. They measure the degree to which the query answer (the set of documents that retrieved by IRs as response to the user query). Where, the query answer is the set of relevant documents in the information based queried. Retrieving most relevant documents to the user query in IRs was one of the most important methods of World Wide Web (WWW) search engines used in the world now. So the searchers aim to use genetic programming (GP) and fuzzy optimization to optimize the user search query in the Boolean IRs model and in the fuzzy IRs model; and to use more Boolean operators (AND, OR, XOR, OF, and NOT) instead of using the standard operators (AND, OR, and NOT), and to use weights for terms and for Boolean operators. Weights are used to give the users more relaxation in defining how much the importance of the terms and of the Boolean operators is. The terms and the Boolean operators' weights are used in fuzzy IRs model. In addition, it investigates extensions of the classical measurement of effectiveness in IRs, precision; recall and harmonic mean. The researchers use harmonic mean measure as an objective function which uses both measures precision and recall at once for evaluating the results of the two IRs models to grow up the precision-recall relationship curve.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2007 Volume:17 | Number:4

Harvested from:

CDK

Metadata only:

false