Advertisement

Search

  • Gerald Kowalski
Chapter

Abstract

The searching algorithms provide the filtering of the indexed items to create an ordered list of items with the most likely relevant items at the top. The search process uses the users query as a starting point in determining what items are most likely relevant to the user. This process revolves around a similarity measure formula that is used along with any heuristics added to improve the basic formula. There are many different similarity measures that are presented along with the rationale behind their use. Search results can be improved when there is feedback from a search on which hits are relevant and which are not—use of relevance feedback. Searches against multimedia items either follow textual search similarity approaches or use proprietary algorithms based upon the specific indexing for the multimedia modality.

Keywords

Similarity Measure Relevance Feedback Query Term Relevant Item Search Statement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer US 2011

Authors and Affiliations

  • Gerald Kowalski
    • 1
  1. 1.AshburnUSA

Personalised recommendations