Articles

While sentence extraction as an approach to summarization has been shown to work in docu- ments of certain genres, because of the conver- sational nature of email communication where utterances are made in relation to one made previously, sentence extraction may not capture the necessary segments of dialogue that would …...

This article describes the results of a systematic in- depth study of the criteria used for word sense disambiguation. Our study is based on 60 target words: 20 nouns, 20 adjectives and 20 verbs. Our results are not always in line with some practices in the field. For example, we …...

In this paper, we discuss the performance of cross- lingual information extraction systems employing an automatic pattern acquisition module. This mod- ule, which creates extraction patterns starting from a user’s narrative task description, allows rapid cus- tomization to new extraction tasks. We compare two approaches: (1) acquiring patterns in the …...

Some Information Extraction (IE) systems are limited to extracting events expressed in a single sentence. It is not clear what ef- fect this has on the difficulty of the extrac- tion task. This paper addresses the prob- lem by comparing a corpus which has been annotated using two separate schemes: …...

s Chun Xiao and Dietmar R¨osner Institut f¨ur Wissens- und Sprachverarbeitung Otto-von-Guericke Universit¨at Magdeburg Universit¨atsplatz 2, Magdeburg, Germany 39106 xiao|roesner@iws.cs.uni-magdeburg.de Abstract In this paper, we investigate the multiword verbs in the English sublanguage of MED- LINE abstracts. Based on the integration of the domain-specific named entity knowledge and syntactic as …...

In this paper we describe a way to discover Named Entities by using the distribution of words in news articles. Named Entity recog- nition is an important task for today’s natural language applications, but it still suffers from data sparseness. We used an observation that a Named Entity is likely …...

We demonstrate that it is possible to perform automatic sentiment classification in the very noisy domain of customer feedback data. We show that by using large feature vectors in combination with feature reduction, we can train linear support vector machines that achieve high classification accuracy on data that present classification …...

This paper proposes a method of automatic back transliteration of proper nouns, in which a Japanese transliterated-word is restored to the original English word. The English words are created from a sequence of letters; thus our method can create new English words that are not registered in dictionaries or English …...

This paper introduces the “Gendercheck Editor”, a tool to check German texts for gender discriminatory formulations. It re- lays on shallow rule-based techniques as used in the Controlled Language Author- ing Technology (CLAT). The paper outlines major sources of gender imbalances in Ger- man texts. It gives a background on …...

We deal with the automated acquisition of a Spanish medical subword lexicon from an al- ready existing Portuguese seed lexicon. Using two non-parallel monolingual corpora we de- termined Spanish lexeme candidates from Por- tuguese seed lexicon entries by heuristic cog- nate mapping. We validated the emergent lex- ical translation hypotheses …...

We present a text mining method for finding synonymous expressions based on the distribu- tional hypothesis in a set of coherent corpora. This paper proposes a new methodology to im- prove the accuracy of a term aggregationsystem using each author’s text as a coherent corpus. Our approach is based on …...

Texts from the medical domain are an important task for natural language processing. This paper investigates the usefulness of a large medical database (the Unified Medical Language System) for the translation of dialogues between doctors and patients using a statistical machine translation system. We are able to show that the …...

The paper presents a new way of accounting for the meaning of verbs in natural languages, using a diagrammatic notation based on the Unified Modeling Language (UML). We will introduce the new framework by outlining some model- ing elements and indicating major differences to the UML. An extended example will …...

In this paper, we present a corpus-based super- vised word sense disambiguation (WSD) sys- tem for Dutch which combines statistical classi- fication (maximum entropy) with linguistic in- formation. Instead of building individual clas- sifiers per ambiguous wordform, we introduce a lemma-based approach. The advantage of this novel method is that …...

We present a novel approach to spoken dialogue summarization. Our system employs a set of semantic similarity metrics using the noun por- tion of WordNet as a knowledge source. So far, the noun senses have been disambiguated man- ually. The algorithm aims to extract utterances carrying the essential content of …...

Although vast amounts of textual data are freely available, many NLP algorithms exploit only a minute percentage of it. In this paper, we study the challenges of working at the terascale. We present an algorithm, designed for the terascale, for mining is-a relations that achieves similar performance to a state-of-the-art …...

Most traditional information extraction approaches are generative models that assume events exist in text in certain patterns and these patterns can be regenerated in various ways. These assumptions limited the syntactic clues being considered for finding an event and confined these approaches to a particular syntactic level. This paper presents …...

* The paper comparatively studies methods of feature weighting in application to the task of cooccurrence-based classification of words according to their meaning. We explore parameter optimization of several weighting methods frequently used for similar problems such as text classification. We find that successful application of all the methods crucially …...

This paper investigates a novel application of sup- port vector machines (SVMs) for sentence reduction. We also propose a new probabilistic sentence reduc- tion method based on support vector machine learn- ing. Experimental results show that the proposed methods outperform earlier methods in term of sen- tence reduction performance. 1...

The reality of analogies between words is re- futed by noone (e.g., I walked is to to walk as I laughed is to to laugh, noted I walked : to walk :: I laughed : to laugh). But computational lin- guists seem to be quite dubious about analogies between sentences: …...