z-logo
open-access-imgOpen Access
Measuring similarity between collection of values
Author(s) -
Carina F. Dorneles,
Carlos A. Heuser,
Andrei E. N. Lima,
Altigran Soares da Silva,
Edleno Silva de Moura
Publication year - 2004
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
ISBN - 1-58113-978-0
DOI - 10.1145/1031453.1031465
Subject(s) - computer science , similarity (geometry) , artificial intelligence , image (mathematics)
In this paper, we propose a set of similarity metrics for manipulating collections of values occuring in XML documents. Following the data model presented in TAX algebra, we treat an XML element as a labeled ordered rooted tree. Consider that XML nodes can be either atomic, i.e, they may contain single values such as short character strings, date, etc, or complex, i.e., nested structures that contain other nodes, we propose two types of similarity metrics: MAVs, for atomic nodes and MCVs, for complex nodes. In the first case, we suggest the use of several application domain dependent metrics. In the second case, we define metrics for complex values that are structure dependent, and can be distinctly applied for it and collections of values. We also present experiments showing the effectiveness of our method.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom