Guest editorial: web information technologies

Abstract

The last decades witnessed the rapid growth of Web technologies, methodologies and applications. This special issue collects eight research papers which are extensions of the best papers of the WISE 2013 conference(14 International Conference of Web Information Systems Engineering, Nanjing, China). The first paper, by Huang et al, “Mining streams of short text for analysis of world-wide event evolutions”, addresses the limitations of existing techniques such as LDA in detecting and tracking events through short text analysis. The authors propose a novel algorithm named FTCCT (Finding Topic Clusters using Co-occurring Terms) to automatically generate topics from a short text corpus, and develop an Event EvolutionMining (EEM) algorithm to discover hot events and their evolutions. Evolutions of the hot events are also visualized in the paper. The second paper, by Li et al., “Social event identification and ranking on flickr”, focuses on social event modeling and ranking. A new method is introduced to effectively identify events by considering the spreading effect of event in the spatio-temporal space, and a selfexciting point process model is developed to capture the triggering relationships among events. Furthermore, event impact is defined and estimated via random walk based on the triggering relationships. Huang et al. study user attribute identification or profile inference in the third paper, “A multi-source integration framework for user occupation inference in social media systems”. The authors propose a comprehensive framework to infer the user occupation from his/her social activities recorded in the micro-blog system, by identifying some beneficial content features and proposing a machine learning classification model.