Deep Web pages convey very relevant information for different application domains like e-government, e-commerce, social networking. For this reason there is a constant high interest in efficiently, effectively and automatically extracting data from Deep ...

To solve the problem of situations with nonlinearly separable clusters, kernel clustering methods have been proposed. Symbolic Data Analysis (SDA) has emerged to deal with variables that can have intervals, histograms, and even functions as values, in ...

In traditional clustering methods, a document is often represented as "bag of words" (in BOW model) or n-grams (in suffix tree document model) without considering the natural language relationships between the words. In this paper, we propose a novel ...

Nonnegative matrix factorization (NMF) is widely used in data mining and machine learning fields. However, many data contain noises and outliers. Thus a robust version of NMF is needed. In this paper, we propose a robust formulation of NMF using L21 ...

Social (or folksonomic) tagging has become a very popular way to describe content within Web 2.0 websites. However, as tags are informally defined, continually changing, and ungoverned, it has often been criticised for lowering, rather than increasing, ...

Measuring the similarity of two records is a challenging problem, but necessary for fundamental tasks, such as duplicate detection and similarity search. By exploiting frequencies of attribute values, many similarity measures can be improved: In a ...

With the increasing in number and size of databases dedicated to the storage of visual content, the need for effective retrieval systems has become crucial. The proposed method makes a significant contribution to meet this need through a technique in ...

Social bookmarking sites typically visualize user-generated tags as tag clouds. While tag clouds effectively show the relative frequency and thus popularity of tags, they fail to convey two aspects to the users: (1) the similarity between tags, and (2) ...