Objectives
The World Wide Web is a huge repository of global information that holds tremendous potential for data mining and knowledge discovery. The diversity and vastness of data on the WWW is both a challenge and an impediment to the successful application of traditional mining and knowledge discovery tools and techniques. The crossover from traditional data sources to the WWW demands new notions, frameworks and solutions to address changes and developments required in equipping data mining and knowledge discovery tools and techniques for the new arena.
This workshop intends to bring together researchers in the knowledge discovery and mining areas and in the management of unstructured and semi-structured Web data areas to assess current methodologies and explore new notions, approaches, and issues in web data mining and warehousing.

Objectives
Most of real-world data involve some irregularity on their formats and data quality. Some data may have certain structures which can not be easily converted to the acceptable formats for the standard KDD methods. Many real-world data contain noise and missing values. Accordingly, KDD on real-world data needs wide variety of techniques involving data selection, preprocessing, format transformation, data mining, interpretation and evaluation. All required techniques should interactively applied and well-tuned to efficiently discover knowledge embedded in the data. The wide and concrete discussion on the practical issues of KDD on real-world data is hardly seen in ordinary presentations of technical conferences.
This workshop intends to bring together many researchers and practitioners interested in the KDD on real-world data and provide the opportunity to discuss the aforementioned issues though tackling some common example data acquired from real-world domains.