Xiaochun Yun (ed.); Weiping Wen (ed.); Bo Lang (ed.); Hanbing Yan (ed.); Li Ding (ed.); Jia Li (ed.); Yu Zhou (ed.) Springer (2019) Pehmeäkantinen kirja
Wei Lu (ed.); Qiaoyan Wen (ed.); Yuqing Zhang (ed.); Bo Lang (ed.); Weiping Wen (ed.); Hanbing Yan (ed.); Chao Li (ed.) Springer (2021) Pehmeäkantinen kirja
Being the de-facto standard for data representation and exchange over the Web, XML (Extensible Markup Language) allows the easy development of applications that exchange data over the Web. This creates a set of data management requirements involving XML. XML and related standards have been extensively applied in many business, service, and multimedia applications. As a result, a large volume of data is managed today directly in XML format. With the wide and in-depth utilization of XML in diverse application domains, some particularities of data management in concrete applications emerge, which challenge current XML technology. This is very similar with the situation that some database models and special database systems have been developed so that databases can satisfy the need of managing diverse data well. In data- and knowledge- intensive application systems, one of the challenges can be generalized as the need to handle imprecise and uncertain information in XML data management by applying fuzzy logic, probability, and more generally soft computing. Currently, two kinds of situations are roughly identified in soft computing for XML data management: applying soft computing for the intelligent processing of classical XML data; applying soft computing for the representation and processing of imprecise and uncertain XML data. For the former, soft computing can be used for flexible query of XML document as well as XML data mining, XML duplicate detection, and so on.
