53 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 3 DOI: 10.4018/978-1-61350-356-0.ch003 INTRODUCTION In recent years, the number of various multi- dimensional data generated and distributed in various information sources as well as the num- ber of users that use these information sources has been increasing. These sources usually use different models for the representation of data, such as the relational model, semistructured models on the web, text files, etc. For efficient data management and exchange, XML has been increasing its relevance as a fundamental standard. As the widespread use of XML for describing and exchanging data on the web is increasing, XML based comparison becomes a central issue in the database and information retrieval. The use of XML similarity in a wide range of applications such as data integration, change management, classification/clustering of XML documents and XML querying is needed (Tekli, Chbeir, & Yetongnon, 2009). Sanjay Kumar Madria Missouri University of Science and Technology, USA Waraporn Viyanon Missouri University of Science and Technology, USA XML Similarity Detection and Measures ABSTRACT XML similarity detection plays an important role in facilitating many applications such as data integra- tion, document classifcation/clustering, querying, and change management. In this chapter, we present an overview on XML document syntactic and semantic similarity/distance measures along with existing research related to XML similarity detection. The measures are classifed into two main categories: structural similarity, and structural and content similarity. We review similarity detection approaches proposed in the literature and discuss some of the challenges and future directions for research on XML similarity detection and related felds.