Word Sense Induction (WSI) is the task of identifying the different uses (senses) of a target word in a given text in an unsupervised manner, i.e. without relying on any external resources such as dictionaries or sense-tagged data. This paper presents a thorough description of the SemEval-2010 WSI task and a new evaluation setting for sense induction methods. Our contributions are two-fold: fir...

The Duluth-WSI systems in SemEval-2 built word co–occurrence matrices from the task test data to create a second order co–occurrence representation of those test instances. The senses of words were induced by clustering these instances, where the number of clusters was automatically predicted. The Duluth-Mix system was a variation of WSI that used the combination of training and test data to cr...

This paper describes our system for shared task 13 “Word Sense Induction for Graded and Non-Graded Senses” of SemEval-2013. The task is on word sense induction (WSI), and builds on earlier SemEval WSI tasks in exploring the possibility of multiple senses being compatible to varying degrees with a single contextual instance: participants are asked to grade senses rather than selecting a single s...

Information-theoretic measures are among the most standard techniques for evaluation of clustering methods including word sense induction (WSI) systems. Such measures rely on sample-based estimates of the entropy. However, the standard maximum likelihood estimates of the entropy are heavily biased with the bias dependent on, among other things, the number of clusters and the sample size. This m...

Digital whole slide imaging (WSI) provides a complement to traditional histopathology assessments of glass tissue slides for toxicologic pathology. WSI allows users to view images of entire slide content, or selected fields at increasing magnifications, and to compare multiple slide images simultaneously. The technology incorporates robust image databases with metadata and search & retrieval ca...

In this paper a novel solution to automatic and unsupervised word sense induction (WSI) is introduced. It represents an instantiation of the ‘one sense per collocation’ observation (Gale et al., 1992). Like most existing approaches it utilizes clustering of word co-occurrences. This approach differs from other approaches to WSI in that it enhances the effect of the one sense per collocation obs...

OBJECTIVES In the present study, we examined the relation between socioeconomic status (SES) and the physiological distribution of iron-related blood parameters. DESIGN This is a cross-sectional analysis of longitudinal population-based cohort study. SETTING Based on a sample of healthy participants from a German research centre, various blood parameters and values of clinical examinations ...

The assessment of surface finish has become increasingly important in the field of precision engineering. Optical interferometry has been widely used for surface measurement due to the advantages of non-contact and high accuracy interrogation. In spite of the 2π phase ambiguity that can limit the measurement scale in monochromatic interferometry, other optical interferomtry have succeeded to ov...

SemEval-2013 Task 13 measures the performance of Word Sense Induction (WSI) and unsupervised Word Sense Disambiguation (WSD) systems. Given a word in context, the systems must label the word with one or more senses, indicating valid interpretations of the word, and where each sense annotation may be accompanied by a weight indicating how likely that interpretation is. Before performing the anno...

Indicators of the impact on freshwater resources are becoming increasingly important in the evaluation of urban water systems. To reveal the importance of spatial resolution, we investigated how the choice of catchment scale influenced the freshwater impact assessment. Two different indicators were used in this study: the Withdrawal-To-Availability ratio (WTA) and the Water Stress Index (WSI). ...