EconPapers    
Economics at your fingertips  
 

Image Retrieval with Textual Label Similarity Features

Alicia Sagae and Scott E. Fahlman

Intelligent Systems in Accounting, Finance and Management, 2015, vol. 22, issue 1, 101-113

Abstract: This article presents a knowledge‐based solution for retrieving English descriptions of images. We analyse the errors made by a baseline system that relies on term frequency, and we find that the task requires deeper semantic representation. Our solution is to perform incremental, task‐driven development of an ontology. Ontological features are then applied in a machine‐learning algorithm for ranking candidate image descriptions. This work demonstrates the advantage of combining knowledge‐based and statistical approaches for text retrieval, and it establishes the important result that an empirically tuned task‐specific ontology performs better than a domain‐general resource like WordNet, even on previously unseen examples. Copyright © 2015 John Wiley & Sons, Ltd.

Date: 2015
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/isaf.1364

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:isacfm:v:22:y:2015:i:1:p:101-113

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=1099-1174

Access Statistics for this article

More articles in Intelligent Systems in Accounting, Finance and Management from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:isacfm:v:22:y:2015:i:1:p:101-113