This book constitutes the refereed proceedings of the Second International Conference on Digital Economy, ICDEc 2017, held in Sidi Bou Said, Tunisia, in May 2017. The 18 papers presented in this volume were carefully reviewed and selected from 46 submissions. The theme of ICDEc 2017 was "Digital Economy: Emerging Technologies and Business Innovation". The conference offered a number of sessions discussing innovative research focusing on emerging technologies which support the digital transformation of business and the economy: digital marketing, digital economy and e-learning, data science and security, and uncertainty in Web data.

This book constitutes the refereed proceedings of the Third International Conference on Advanced Data Mining and Applications, ADMA 2007, held in Harbin, China in August 2007.

The 44 revised full papers and 15 revised short papers presented together with the abstract of 1 invited lecture were carefully reviewed and selected from about 200 submissions. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining. The major theme of the conference encompasses the innovative applications of data mining approaches to real-world problems that involve large data sets, incomplete and noisy data, or demand optimal solutions.

Here are the proceedings of the 2nd International Conference on Advanced Data Mining and Applications, ADMA 2006, held in Xi'an, China, August 2006. The book presents 41 revised full papers and 74 revised short papers together with 4 invited papers. The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, and more.

1 WorkshopTheme Digital multimedia di?ers from previous forms of combined media in that the bits that represent text, images, animations, and audio, video and other signals can be treated as data by computer programs. One facet of this diverse data in termsofunderlyingmodelsandformatsisthatitissynchronizedandintegrated, hence it can be treated as integral data records. Such records can be found in a number of areas of human endeavour. Modern medicine generates huge amounts of such digital data. Another - ample is architectural design and the related architecture, engineering and c- struction (AEC) industry. Virtual communities (in the broad sense of this word, which includes any communities mediated by digital technologies) are another example where generated data constitutes an integral data record. Such data may include data about member pro?les, the content generated by the virtual community, and communication data in di?erent formats, including e-mail, chat records, SMS messages, videoconferencing records. Not all multimedia data is so diverse. An example of less diverse data, but data that is larger in terms of the collected amount, is that generated by video surveillance systems, where each integral data record roughly consists of a set of time-stamped images - the video frames. In any case, the collection of such in- gral data records constitutes a multimedia data set. The challenge of extracting meaningful patterns from such data sets has led to the research and devel- ment in the area of multimedia data mining.

1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that - dress the unique challenges of discovering insights from Web usage data, aiming toevaluateWebusability, understandtheinterestsandexpectationsofusersand assess the e?ectiveness of content delivery. The maturing and expanding Web presents a key driving force in the rapid growth of electronic commerce and a new channel for content providers. Customized o?ers and content, made possible by discovered knowledge about the customer, are fundamental for the establi- ment of viable e-commerce solutions and sustained and e?ective content delivery in noncommercial domains. Rich Web logs provide companies with data about their online visitors and prospective customers, allowing microsegmentation and personalized interactions. While Web mining as a domain is several years old, the challenges that characterize data analysis in this area continue to be formidable. Though p- processing data routinely takes up a major part of the e?ort in data mining, Web usage data presents further challenges based on the di?culties of assigning data streams to unique users and tracking them over time. New innovations are required to reliably reconstruct sessions, to ascertain similarity and di?erences between sessions, and to be able to segment online users into relevant groups