The extraction of data exemplifying relations between terms can make use, at least to a large extent, of techniques that are similar to those used in standard hybrid term candidate extraction, namely basic corpus analysis tools (e.g. tagging, lemmatization, parsing), as well as morphological analysis of complex words (compounds and derived items). In this article, we discuss the use of such tec...

This paper presents a bootstrapping process that learns linguistically rich extraction patterns for subjective (opinionated) expressions. High-precision classifiers label unannotated data to automatically create a large training set, which is then given to an extraction pattern learning algorithm. The learned patterns are then used to identify more subjective sentences. The bootstrapping proces...

Emotionally-aware Man-Machine Interaction (MMI) systems are presently at the forefront of interest of the computer vision and artificial intelligence communities, since they give the opportunity to less technology-aware people to use computers more efficiently, overcoming fears and preconceptions. Most emotion-related facial and body gestures are considered to be universal, in the sense that th...

Compared to the amount of research that has been done on English event extraction, there exists relatively little work on Chinese event extraction. We seek to push the frontiers of supervised Chinese event extraction research by proposing two extension to Li et al.'s (2012) state-of-the-art event extraction system. First, we employ a joint modeling approach to event extraction, aiming to addres...

Extracting data from web pages using wrappers is a fundamental problem arising in a large variety of applications of vast practical interests. In this paper, we propose a novel technique to the problem of differentiating roles of data items from Web pages, which is one of the key problems in our automatic extraction approach. The problem is resolved at various levels: semantic blocks, sections ...

Important information is captured in medical documents. To make use of this information and intepret the semantics, technologies are required for extracting, analysing and interpreting it. As a result, rich semantics including relations among events, subjectivity or polarity of events, become available. The First Workshop on Extraction and Processing of Rich Semantics from Medical Texts, is dev...

This paper describes the collection, annotation and linguistic analysis of a gold standard for knowledge-rich context extraction on the basis of Russian and German web corpora as part of ongoing PhD thesis work. In the following sections, the concept of knowledge-rich contexts is refined and gold standard creation is described. Linguistic analyses of the gold standard data and their results are...

In this paper the extraction of oils from trout waste is investigated. Trout heads, viscera and spine, obtained from a fish-processing company, have been separately freeze-dried and then extracted. Two different solvent extraction techniques have been utilized and compared: the common soxhlet extraction, which utilizes n-hexane at atmospheric pressure as solvent, and the supercritical CO2 extra...

Existing social collaboration projects contain a host of conceptual knowledge, but are often only sparsely structured and hardly machine-accessible. Using the well known Wikipedia as a showcase, we propose new and improved techniques for extracting ontology data from the wiki category structure. Applications like information extraction, data classification, or consistency checking require ontol...

Biomedical Natural Language Processing (BioNLP) attempts to capture biomedical phenomena from texts by extracting relations between biomedical entities (i.e. proteins and genes). Traditionally, only binary relations have been extracted from large numbers of published papers. Recently, more complex relations (biomolecular events) have also been extracted. Such events may include several entities...