Discovering knowledge from textual sources and subsequently expanding the coverage of knowledge bases like DBPedia or Freebase currently requires either extensive manual work or carefully designed information extractors. Information extractors capture triples from textual sentences. Each triple consists of a subject, a predicate/property, and an object. Triples can be mediated via verbs, nouns,...

This article describes a method of classifying webpages using features extracted from the design. Design features are language independent and correspond well to a user’s first impression of a page. A number of new feature extractors were developed, capable of extracting human-readable features. These features are based on guidelines for use of color and composition in web design. The compositi...

With the increasing number of personal albums and photos in them, users have more and more problems with their organization [4]. This is due to lack of descriptive data, however, their amount only depends on the abilities and will of the image owners. Tools for metadata creation are available – the main problem is with the user motivation: because tagging and annotating of photos is usually a b...

Music tag words that describe music audio by text have different levels of abstraction. Taking this issue into account, we propose a music classification approach that aggregates multilevel and multi-scale features using pre-trained feature extractors. In particular, the feature extractors are trained in sample-level deep convolutional neural networks using raw waveforms. We show that this appr...

I will survey some of the recent exciting progress on explicit constructions of randomness extractors for independent sources. Many of the new constructions rely on explicit constructions of newly introduced pseudorandom primitives, and there remains scope of finding better explicit constructions of these primitives. I will also discuss some possible approaches for constructing optimal Ramsey g...

This paper presents and evaluates two linear feature extractors based on mutual information. These feature extractors consider general dependencies between features and class labels, as opposed to statistical techniques such as PCA which does not consider class labels and LDA, which uses only simple rst order dependencies. As evidenced by several simulations on high dimensional data sets, the p...

Protecting our environment and natural resources is a major global challenge. “Protectors” (law enforcement agencies) try to protect these natural resources, while “extractors” (criminals) seek to exploit them. In many domains, such as illegal fishing, the extractors know more about the distribution and richness of the resources than the protectors, making it extremely difficult for the protect...

In this paper, we take the concept of benchmarking as used extensively in computing and apply it to evaluating C++ fact extractors. We demonstrated the efficacy of this approach by developing a prototype benchmark, CppETS 1.0 (C++ Extractor Test Suite, pronounced see-pets) and collecting feedback in a workshop setting. The CppETS benchmark characterises C++ extractors along two dimensions: Accu...