In this paper, we present a polynomial-time algorithm for TPQ (tree pattern queries) minimization without XML constraints involved. The main idea of the algorithm is a dynamic programming strategy to find all the matching subtrees within a TPQ. A matching subtree implies a redundancy and should be removed in such a way that the semantics of the original TPQ is not damaged. Our algorithm consist...

As a technology based on database, statistics and AI, data mining provides biological research a useful information analyzing tool. The key factors which influence the performance of biological data mining approaches are the large-scale of biological data and the high similarities among patterns mined. In this paper, we present an efficient algorithm named IRTM for mining frequent subtrees embe...

We introduce an approach to learn discriminative visual representations while exploiting external semantic knowledge about object category relationships. Given a hierarchical taxonomy that captures semantic similarity between the objects, we learn a corresponding tree of metrics (ToM). In this tree, we have one metric for each non-leaf node of the object hierarchy, and each metric is responsibl...

The amount of available data has been growing significantly over the last decades. Thus, linking entries across heterogeneous data sources such as databases or knowledge bases, becomes an increasingly difficult problem, in particular w.r.t. the runtime of these tasks. Consequently, it is of utmost importance to provide time-efficient approaches for similarity joins in the Web of Data. While a n...

The first task of statistical computational linguistics, or any other type of datadriven processing of language, is the extraction of counts and distributions of phenomena. This is much more difficult for the type of complex structured data found in treebanks and in corpora with sophisticated annotation than for tokenized texts. Recent developments in data mining, particularly in the extraction...