Not logged in : Login

About: Rocchio algorithm     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : owl:Thing, within Data Space : ods-qa.openlinksw.com:8896 associated with source document(s)

The Rocchio algorithm is based on a method of relevance feedback found in information retrieval systems which stemmed from the SMART Information Retrieval System developed between 1960 and 1964. Like many other retrieval systems, the Rocchio algorithm was developed using the vector space model. Its underlying assumption is that most users have a general conception of which documents should be denoted as relevant or irrelevant. Therefore, the user's search query is revised to include an arbitrary percentage of relevant and irrelevant documents as a means of increasing the search engine's recall, and possibly the precision as well. The number of relevant and irrelevant documents allowed to enter a query is dictated by the weights of the a, b, c variables listed below in the Algorithm section

AttributesValues
sameAs
wasDerivedFrom
dbpedia-owl:abstract
  • The Rocchio algorithm is based on a method of relevance feedback found in information retrieval systems which stemmed from the SMART Information Retrieval System developed between 1960 and 1964. Like many other retrieval systems, the Rocchio algorithm was developed using the vector space model. Its underlying assumption is that most users have a general conception of which documents should be denoted as relevant or irrelevant. Therefore, the user's search query is revised to include an arbitrary percentage of relevant and irrelevant documents as a means of increasing the search engine's recall, and possibly the precision as well. The number of relevant and irrelevant documents allowed to enter a query is dictated by the weights of the a, b, c variables listed below in the Algorithm section.
dbpedia-owl:thumbnail
dbpedia-owl:wikiPageExternalLink
dbpedia-owl:wikiPageID
dbpedia-owl:wikiPageRevisionID
comment
  • The Rocchio algorithm is based on a method of relevance feedback found in information retrieval systems which stemmed from the SMART Information Retrieval System developed between 1960 and 1964. Like many other retrieval systems, the Rocchio algorithm was developed using the vector space model. Its underlying assumption is that most users have a general conception of which documents should be denoted as relevant or irrelevant. Therefore, the user's search query is revised to include an arbitrary percentage of relevant and irrelevant documents as a means of increasing the search engine's recall, and possibly the precision as well. The number of relevant and irrelevant documents allowed to enter a query is dictated by the weights of the a, b, c variables listed below in the Algorithm section
label
  • Rocchio algorithm
dbpprop:wikiPageUsesTemplate
topic
depiction
  • External Image
Subject
is primary topic of
dbpedia-owl:wikiPageLength
dbpedia-owl:wikiPageWikiLink
is sameAs of
is dbpedia-owl:wikiPageRedirects of
is primary topic of
is dbpedia-owl:wikiPageWikiLink of
is inDataset of
Faceted Search & Find service v1.17_git55 as of Mar 01 2021


Alternative Linked Data Documents: ODE     Content Formats:       RDF       ODATA       Microdata      About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 08.03.3322 as of Mar 14 2022, on Linux (x86_64-generic-linux-glibc25), Single-Server Edition (7 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software