Articles

We describe a cross-corpora evaluation of disease mention recognition for two an- notated biomedical corpora: the Human Variome Project Corpus and the Arizona Disease Corpus. Our analysis of the per- formance of a state-of-the-art NER tool in terms of the characteristics and annotation schema of these corpora shows that these …...

This paper presents a notification system to identify in near-real-time Tweets de- scribing fire events in Australia. The sys- tem identifies fire related ‘alert words’ published on Twitter which are further processed by a classifier to determine if they correspond to an actual fire event. We describe how the classifier …...

We compared the performances of two proce- dures for calculating the likelihood ratio (LR) on the same set of text data. The first proce- dure was a multivariate kernel density (MVKD) procedure which has been success- fully applied to various types of forensic evi- dence, including glass fragments, handwriting, fingerprint, …...

Relating one’s research to the vast body of scientific knowledge is a difficult task; the sheer volume of literature makes it diffi- cult to keep up-to-date with scientific de- velopments. Particularly when research is on-going, keeping track of related work is especially important to avoid an unin- tended duplication of …...

Quote attribution is the task of identify- ing the speaker of each quote within a document. While recent research has es- tablished large-scale corpora for this task, these corpora are not yet consistent in the way they handle candidate speakers, and many of the reported results rely on gold standard …...

In Australian healthcare, failures in infor- mation flow cause over one-tenth of pre- ventable adverse events and are tangible in clinical handover. Regardless of a good verbal handover, anything from two-thirds to all of this information is lost after 3– 5 shifts if notes are taken by hand or not …...

Clustering the results of a search can help a multi-document summarizer present a summary for evidence based medicine (EBM). In this work, we introduce a clus- tering technique that is based on multi- objective (MOO) optimization. MOO is a technique that shows promise in the areas of machine learning and …...

This study is an investigation into the effect of sample size on a likelihood ratio (LR) based forensic voice comparison (FVC) system. In particular, we looked into how the offender and suspect sample size (or the within-speaker sample size) would affect the performance of the FVC system, using spectral feature …...

Human evaluation of machine translation quality is a key element in the develop- ment of machine translation systems, as automatic metrics are validated through correlation with human judgment. How- ever, achievement of consistent human judgments of machine translation is not easy, with decreasing levels of consis- tency reported in annual …...

We investigate national dialect identifica- tion, the task of classifying English doc- uments according to their country of ori- gin. We use corpora of known national origin as a proxy for national dialect. In order to identify general (as opposed to corpus-specific) characteristics of national dialects of English, we make …...

In this paper, we discuss how statements about defaults and various forms of excep- tions to them can be incorporated into an existing controlled natural language. We show how these defaults and exceptions are translated and represented in the an- swer set programming paradigm in order to support automated reasoning. …...

In this paper we present a case study fo- cusing on the literature genre, in partic- ular on Italian fictional prose, aimed at identifying the features characterizing this text type. Identified features were tested in two classification tasks, i.e. by genre and by readability, with promising results. Interestingly, the same …...

This paper presents a novel approach to spell checking using dictionary cluster- ing. The main goal is to reduce the num- ber of times distances have to be calcu- lated when finding target words for mis- spellings. The method is unsupervised and combines the application of anomalous pattern initialization and …...

In this paper, we propose a novel method for generating a coarse-grained sense in- ventory from Wikipedia using a ma- chine learning framework. Structural and content-based features are employed to in- duce clusters of articles representative of a word sense. Additionally, multilingual features are shown to improve the clus- tering …...

Part-of-speech information is a pre-requisite in many NLP algorithms. However, Twitter text is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We present a detailed error analysis of exist- ing taggers, motivating a series of tagger aug- mentations which are demonstrated to improve performance. We …...

This paper reports on the annotation and maximum-entropy modeling of the se- mantics of two German prepositions, mit (‘with’) and auf (‘on’). 500 occurrences of each preposition were sampled from a treebank and annotated with syntacto- semantic classes by two annotators. The classification is guided by a perspective of information …...

In this paper we propose a method for identifying cognates based on etymology and etymons. We employ this approach to evaluate the extent to which lexical simi- larity can be used for automatic detection of cognate pairs. We investigate some or- thographic approaches widely used in this research area and …...

This paper describes a phrase-based ma- chine translation approach to normalize Dutch user-generated content (UGC). We compiled a corpus of three different so- cial media genres (text messages, message board posts and tweets) to have a sample of this recent domain. We describe the var- ious characteristics of this noisy …...

In this paper we look at a task in historical linguistics and the study of language de- velopment, namely that of identifying the time when a text was written. The nov- elty is that we evaluate our classifier and our selected features on literary texts hav- ing their action placed …...

In this study, we measure the contribution of different event components and particular se- mantic relations to the task of event coreference resolution. First we calculate what event times, locations and participants add to event coreference resolution. Secondly, we an- alyze the contribution by hyponymy and gran- ularity within the …...