ACM Transactions on Knowledge Discovery from Data

With the rapid growth of modern technologies, Internet has reached almost every corner of the world. As a result, it becomes more and more important to manage and mine information contained in Web pages in different languages. Traditional supervised ...

Social influence analysis has shown great potential for strategic marketing decision. It is well known that people influence one another based on both their social connections and the social activities that they have engaged in the past. In this article,...

How can we efficiently decompose a tensor into sparse factors, when the data do not fit in memory? Tensor decompositions have gained a steadily increasing popularity in data-mining applications; however, the current state-of-art decomposition algorithms ...

Computational methods and tools that can efficiently and effectively analyze the temporal changes in dynamic complex relational networks enable us to gain significant insights regarding the entity relations and their evolution. This article introduces a ...

An integrated framework for density-based cluster analysis, outlier detection, and data visualization is introduced in this article. The main module consists of an algorithm to compute hierarchical estimates of the level sets of a density, following ...

Semiautomated Text Classification (SATC) may be defined as the task of ranking a set D of automatically labelled textual documents in such a way that, if a human annotator validates (i.e., inspects and corrects where appropriate) the documents in a top-...

During the last decade, microblog has become an important social networking service with billions of users all over the world, acting as a novel and efficient platform for the creation and dissemination of real-time information. Modeling and revealing ...

Traditional clustering algorithms deal with a single clustering task on a single dataset. However, there are many related tasks in the real world, which motivates multitask clustering. Recently some multitask clustering algorithms have been proposed, ...

Given social networks over time, how can we measure network activities across different timesteps with a limited number of metrics? We propose two classes of dynamic metrics for assessing temporal evolution patterns of agents in terms of persistency and ...

The availability of trajectories tracking the geographical locations of people as a function of time offers an opportunity to study human behaviors. In this article, we study rationality from the perspective of user decision on visiting a point of ...