Roman Klinger

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Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions. A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721. Here we present brief descriptions of all(More)
MOTIVATION Chemical compounds like small signal molecules or other biological active chemical substances are an important entity class in life science publications and patents. Several representations and nomenclatures for chemicals like SMILES, InChI, IUPAC or trivial names exist. Only SMILES and InChI names allow a direct structure search, but in(More)
Irony is an important device in human communication, both in everyday spoken conversations as well as in written texts including books, websites, chats, reviews, and Twitter messages among others. Specific cases of irony and sarcasm have been studied in different contexts but, to the best of our knowledge, only recently the first publicly available corpus(More)
Most relation extraction methods, especially in the domain of biology, rely on machine learning methods to classify a cooccurring pair of entities in a sentence to be related or not. Such an approach requires a training corpus, which involves expert annotation and is tedious, timeconsuming, and expensive. We overcome this problem by the use of existing(More)
Chemical compounds like small signal molecules or other biological active chemical substances are an important entity class in life science publications and patents. The recognition of these named entities relies on appropriate dictionary resources as well as on training and evaluation corpora. In this work we give an overview of publicly available chemical(More)
The Gene Mention task is a Named Entity Recognition (NER) task for labeling gene and gene product names in biomedical text. To deal with acceptable alternatives additionally to the gold standard, we use combinations of Conditional Random Fields (CRF) together with a normalizing tagger. This process is followed by a postprocessing step including an acronym(More)
INTRODUCTION MicroRNAs (miRNAs) have demonstrated their potential as post-transcriptional gene expression regulators, participating in a wide spectrum of regulatory events such as apoptosis, differentiation, and stress response. Apart from the role of miRNAs in normal physiology, their dysregulation is implicated in a vast array of diseases. Dissection of(More)
Opinion mining is often regarded as a classification or segmentation task, involving the prediction of i) subjective expressions, ii) their target and iii) their polarity. Intuitively, these three variables are bidirectionally interdependent, but most work has either attempted to predict them in isolation or proposing pipeline-based approaches that cannot(More)
Sentiment analysis and opinion mining are often addressed as a text classification or entity recognition problem, involving the detection or classification of aspects and subjective phrases. Many approaches do not model the relation between aspects and subjective phrases explicitly, implicitly assuming that a subjective phrase refers to a certain aspect if(More)