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A survey of automatic term extraction for Brazilian Portuguese

Conrado, Merley da Silva; Felippo, Ariani Di; Pardo, Thiago Alexandre Salgueiro; Rezende, Solange Oliveira
Fonte: Springer; Dordrecht Publicador: Springer; Dordrecht
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
96.25%
Background: Term extraction is highly relevant as it is the basis for several tasks, such as the building of dictionaries, taxonomies, and ontologies, as well as the translation and organization of text data. Methods and Results: In this paper, we present a survey of the state of the art in automatic term extraction (ATE) for the Brazilian Portuguese language. In this sense, the main contributions and projects related to such task have been classified according to the knowledge they use: statistical, linguistic, and hybrid (statistical and linguistic). We also present a study/review of the corpora used in the term extraction in Brazilian Portuguese, as well as a geographic mapping of Brazil regarding such contributions, projects, and corpora, considering their origins. Conclusions: In spite of the importance of the ATE, there are still several gaps to be filled, for instance, the lack of consensus regarding the formal definition of meaning of ‘term’. Such gaps are larger for the Brazilian Portuguese when compared to other languages, such as English, Spanish, and French. Examples of gaps for Brazilian Portuguese include the lack of a baseline ATE system, as well as the use of more sophisticated linguistic information, such as the WordNet and Wikipedia knowledge bases. Nevertheless...

Extração de termos de manuais técnicos de produtos tecnológicos: uma aplicação em Sistemas de Adaptação Textual; Term extraction from technological products instruction manuals: an application in textual adaptation systems

Muniz, Fernando Aurélio Martins
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 28/04/2011 PT
Relevância na Pesquisa
86.12%
No Brasil, cerca de 68% da população é classificada como leitores com baixos níveis de alfabetização, isto é, possuem o nível de alfabetização rudimentar (21%) ou básico (47%), segundo dados do INAF (2009). O projeto PorSimples utilizou as duas abordagens de Adaptação Textual, a Simplificação e a Elaboração, para ajudar leitores com baixo nível de alfabetização a compreender documentos disponíveis na Web em português do Brasil, principalmente textos jornalísticos. Esta pesquisa de mestrado também se dedicou às duas abordagens acima, mas o foco foi o gênero de textos instrucionais. Em tarefas que exigem o uso de documentação técnica, a qualidade da documentação é um ponto crítico, pois caso a documentação seja imprecisa, incompleta ou muito complexa, o custo da tarefa ou até mesmo o risco de acidentes aumenta muito. Manuais de instrução possuem duas relações procedimentais básicas: a relação gera generation (quando uma ação gera automaticamente uma ação ), e a relação habilita enablement (quando a realização de uma ação permite a realização da ação , mas o agente precisa fazer algo a mais para garantir que irá ocorrer). O projeto aqui descrito, intitulado NorMan, estudou como as relações procedimentais gera e habilita são realizadas em manuais de instruções...

Extração automática de termos simples baseada em aprendizado de máquina; Automatic simple term extraction based on machine learning

Laguna, Merley da Silva Conrado
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 06/05/2014 PT
Relevância na Pesquisa
86.49%
A Mineração de Textos (MT) visa descobrir conhecimento inovador nos textos não estruturados. A extração dos termos que representam os textos de um domínio é um dos passos mais importantes da MT, uma vez que os resultados de todo o processo da MT dependerão, em grande parte, da qualidade dos termos obtidos. Nesta tese, considera-se como termos as unidades lexicais realizadas para designar conceitos em um cenário tematicamente restrito. Para a extração dos termos, pode-se fazer uso de abordagens como: estatística, linguística ou híbrida. Normalmente, para a Mineração de Textos, são utilizados métodos estatísticos. A aplicação desses métodos é computacionalmente menos custosa que a dos métodos linguísticos, entretanto seus resultados são geralmente menos interpretáveis. Ambos métodos, muitas vezes, não são capazes de identificar diferenças entre termos e não-termos, por exemplo, os estatísticos podem não identificar termos raros ou que têm a mesma frequência de não-termos e os linguísticos podem não distinguir entre termos que seguem os mesmo padrões linguísticos dos não-termos. Uma solução para esse problema é utilizar métodos híbridos, de forma a combinar as estratégias dos métodos linguísticos e estatísticos...

Automatic preservation watch using information extraction on the Web : a case study on semantic extraction of natural language for digital preservation

Faria, Luís; Akbik, Alan; Sierman, Barbara; Ras, Marcel; Ferreira, Miguel; Ramalho, José Carlos
Fonte: Biblioteca Nacional de Portugal Publicador: Biblioteca Nacional de Portugal
Tipo: Conferência ou Objeto de Conferência
Publicado em /09/2013 ENG
Relevância na Pesquisa
46.14%
The ability to recognize when digital content is becoming endangered is essential for maintaining the long-term, continuous and authentic access to digital assets. To achieve this ability, knowledge about aspects of the world that might hinder the preservation of content is needed. However, the processes of gathering, managing and reasoning on knowledge can become manually infeasible when the volume and heterogeneity of content increases, multiplying the aspects to monitor. Automation of these processes is possible [11,21], but its usefulness is limited by the data it is able to gather. Up to now, automatic digital preservation processes have been restricted to knowledge expressed in a machine understandable language, ignoring a plethora of data expressed in natural language, such as the DPC Technology Watch Reports, which could greatly contribute to the completeness and freshness of data about aspects of the world related to digital preservation. This paper presents a real case scenario from the National Library of the Netherlands, where the monitoring of publishers and journals is needed. This knowledge is mostly represented in natural language on Web sites of the publishers and, therefore, is dificult to automatically monitor. In this paper...

Automatic extraction of concepts from texts and applications

Ventura, João Miguel Jones
Fonte: Universidade Nova de Lisboa Publicador: Universidade Nova de Lisboa
Tipo: Tese de Doutorado
Publicado em /05/2014 ENG
Relevância na Pesquisa
26.05%
The extraction of relevant terms from texts is an extensively researched task in Text- Mining. Relevant terms have been applied in areas such as Information Retrieval or document clustering and classification. However, relevance has a rather fuzzy nature since the classification of some terms as relevant or not relevant is not consensual. For instance, while words such as "president" and "republic" are generally considered relevant by human evaluators, and words like "the" and "or" are not, terms such as "read" and "finish" gather no consensus about their semantic and informativeness. Concepts, on the other hand, have a less fuzzy nature. Therefore, instead of deciding on the relevance of a term during the extraction phase, as most extractors do, I propose to first extract, from texts, what I have called generic concepts (all concepts) and postpone the decision about relevance for downstream applications, accordingly to their needs. For instance, a keyword extractor may assume that the most relevant keywords are the most frequent concepts on the documents. Moreover, most statistical extractors are incapable of extracting single-word and multi-word expressions using the same methodology. These factors led to the development of the ConceptExtractor...

Automatic Extraction of Protein Point Mutations Using a Graph Bigram Association

Lee, Lawrence C; Horn, Florence; Cohen, Fred E
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
25.91%
Protein point mutations are an essential component of the evolutionary and experimental analysis of protein structure and function. While many manually curated databases attempt to index point mutations, most experimentally generated point mutations and the biological impacts of the changes are described in the peer-reviewed published literature. We describe an application, Mutation GraB (Graph Bigram), that identifies, extracts, and verifies point mutations from biomedical literature. The principal problem of point mutation extraction is to link the point mutation with its associated protein and organism of origin. Our algorithm uses a graph-based bigram traversal to identify these relevant associations and exploits the Swiss-Prot protein database to verify this information. The graph bigram method is different from other models for point mutation extraction in that it incorporates frequency and positional data of all terms in an article to drive the point mutation–protein association. Our method was tested on 589 articles describing point mutations from the G protein–coupled receptor (GPCR), tyrosine kinase, and ion channel protein families. We evaluated our graph bigram metric against a word-proximity metric for term association on datasets of full-text literature in these three different protein families. Our testing shows that the graph bigram metric achieves a higher F-measure for the GPCRs (0.79 versus 0.76)...

Automatic extraction of topic hierarchies based on WordNet

Brey, Gerhard; Vieira, Miguel
Fonte: Australasian Association for Digital Humanities Publicador: Australasian Association for Digital Humanities
Tipo: Conference item Formato: 20 slides, Powerpoint presentation
Relevância na Pesquisa
36%
The aim of the research described here is the automatic generation of a topic hierarchy, using WordNet as the basis for a faceted browser interface, with a collection of 19th-century periodical texts as the test corpus. Our research was motivated by the Castanet algorithm, which was developed and successfully applied to short descriptions of documents. In our research we adapt the algorithm so that it can be applied to the full text of documents. The algorithm for the automatic generation of the topic hierarchy has three main processes: Data preparation, wherein data is prepared so that the information contained within the texts is more easily accessible; Target term extraction, wherein terms that are considered relevant to classify each text are selected, and; Topic tree generation, wherein the tree is built using the target terms. We evaluated samples of the resulting topic tree and found that over 90% of the topics are relevant, i.e. they clearly illustrate what the articles are about and the topic hierarchy adequately relates to the content of the articles. Future work will address problems resulting from mis‐OCRed words, erroneous disambiguation, and language anachronisms. Faceted browsing interfaces based on topic hierarchies are easy and intuitive to navigate...

Radar techniques for human gait automatic recognition

FORTUNY GUASCH Joaquim; SAMMARTINO PIER FRANCESCO
Fonte: IEEE Publicador: IEEE
Tipo: Contributions to Conferences Formato: CD-ROM
ENG
Relevância na Pesquisa
25.84%
In this paper we extend the investigation on the use of Doppler signatures for human motion detection. As it is well known, human movements generate additional Doppler frequencies on top of the main Doppler carrier. In recent times research has been trying to exploit this effect for dynamic feature extraction and, consequently, automatic target recognition. Here a simulation tool is developed and measurements are presented as a term of comparison. Several scenarios that model arbitrary trajectories and multiple targets are analyzed. Finally we provide an insight into the potential using more than one sensor. This may improve dramatically the performance of the system as it does in many other radar applications.; JRC.G.6-Security technology assessment

Élaboration d'un corpus étalon pour l'évaluation d'extracteurs de termes

Bernier-Colborne, Gabriel
Fonte: Université de Montréal Publicador: Université de Montréal
Tipo: Thèse ou Mémoire numérique / Electronic Thesis or Dissertation
FR
Relevância na Pesquisa
26.13%
Ce travail porte sur la construction d’un corpus étalon pour l’évaluation automatisée des extracteurs de termes. Ces programmes informatiques, conçus pour extraire automatiquement les termes contenus dans un corpus, sont utilisés dans différentes applications, telles que la terminographie, la traduction, la recherche d’information, l’indexation, etc. Ainsi, leur évaluation doit être faite en fonction d’une application précise. Une façon d’évaluer les extracteurs consiste à annoter toutes les occurrences des termes dans un corpus, ce qui nécessite un protocole de repérage et de découpage des unités terminologiques. À notre connaissance, il n’existe pas de corpus annoté bien documenté pour l’évaluation des extracteurs. Ce travail vise à construire un tel corpus et à décrire les problèmes qui doivent être abordés pour y parvenir. Le corpus étalon que nous proposons est un corpus entièrement annoté, construit en fonction d’une application précise, à savoir la compilation d’un dictionnaire spécialisé de la mécanique automobile. Ce corpus rend compte de la variété des réalisations des termes en contexte. Les termes sont sélectionnés en fonction de critères précis liés à l’application...

Analyse comparative de l'équivalence terminologique en corpus parallèle et en corpus comparable : application au domaine du changement climatique

Le Serrec, Annaïch
Fonte: Université de Montréal Publicador: Université de Montréal
Tipo: Thèse ou Mémoire numérique / Electronic Thesis or Dissertation
FR
Relevância na Pesquisa
45.96%
Les travaux entrepris dans le cadre de la présente thèse portent sur l’analyse de l’équivalence terminologique en corpus parallèle et en corpus comparable. Plus spécifiquement, nous nous intéressons aux corpus de textes spécialisés appartenant au domaine du changement climatique. Une des originalités de cette étude réside dans l’analyse des équivalents de termes simples. Les bases théoriques sur lesquelles nous nous appuyons sont la terminologie textuelle (Bourigault et Slodzian 1999) et l’approche lexico-sémantique (L’Homme 2005). Cette étude poursuit deux objectifs. Le premier est d’effectuer une analyse comparative de l’équivalence dans les deux types de corpus afin de vérifier si l’équivalence terminologique observable dans les corpus parallèles se distingue de celle que l’on trouve dans les corpus comparables. Le deuxième consiste à comparer dans le détail les équivalents associés à un même terme anglais, afin de les décrire et de les répertorier pour en dégager une typologie. L’analyse détaillée des équivalents français de 343 termes anglais est menée à bien grâce à l’exploitation d’outils informatiques (extracteur de termes, aligneur de textes, etc.) et à la mise en place d’une méthodologie rigoureuse divisée en trois parties. La première partie qui est commune aux deux objectifs de la recherche concerne l’élaboration des corpus...

Automatic Application Level Set Approach in Detection Calcifications in Mammographic Image

Boujelben, Atef; Tmar, Hedi; Mnif, Jameleddine; Abid, Mohamed
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 01/09/2011
Relevância na Pesquisa
25.92%
Breast cancer is considered as one of a major health problem that constitutes the strongest cause behind mortality among women in the world. So, in this decade, breast cancer is the second most common type of cancer, in term of appearance frequency, and the fifth most common cause of cancer related death. In order to reduce the workload on radiologists, a variety of CAD systems; Computer-Aided Diagnosis (CADi) and Computer-Aided Detection (CADe) have been proposed. In this paper, we interested on CADe tool to help radiologist to detect cancer. The proposed CADe is based on a three-step work flow; namely, detection, analysis and classification. This paper deals with the problem of automatic detection of Region Of Interest (ROI) based on Level Set approach depended on edge and region criteria. This approach gives good visual information from the radiologist. After that, the features extraction using textures characteristics and the vector classification using Multilayer Perception (MLP) and k-Nearest Neighbours (KNN) are adopted to distinguish different ACR (American College of Radiology) classification. Moreover, we use the Digital Database for Screening Mammography (DDSM) for experiments and these results in term of accuracy varied between 60 % and 70% are acceptable and must be ameliorated to aid radiologist.; Comment: 14 pages...

A Study of Association Measures and their Combination for Arabic MWT Extraction

Mahdaouy, Abdelkader El; Ouatik, Saïd EL Alaoui; Gaussier, Eric
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 10/09/2014
Relevância na Pesquisa
36.02%
Automatic Multi-Word Term (MWT) extraction is a very important issue to many applications, such as information retrieval, question answering, and text categorization. Although many methods have been used for MWT extraction in English and other European languages, few studies have been applied to Arabic. In this paper, we propose a novel, hybrid method which combines linguistic and statistical approaches for Arabic Multi-Word Term extraction. The main contribution of our method is to consider contextual information and both termhood and unithood for association measures at the statistical filtering step. In addition, our technique takes into account the problem of MWT variation in the linguistic filtering step. The performance of the proposed statistical measure (NLC-value) is evaluated using an Arabic environment corpus by comparing it with some existing competitors. Experimental results show that our NLC-value measure outperforms the other ones in term of precision for both bi-grams and tri-grams.; Comment: This paper have been presented and published in 10th International Conference on Terminology and Artificial Intelligence Proceedings

A tool set for the quick and efficient exploration of large document collections

Ignat, Camelia; Pouliquen, Bruno; Steinberger, Ralf; Erjavec, Tomaz
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 12/09/2006
Relevância na Pesquisa
25.84%
We are presenting a set of multilingual text analysis tools that can help analysts in any field to explore large document collections quickly in order to determine whether the documents contain information of interest, and to find the relevant text passages. The automatic tool, which currently exists as a fully functional prototype, is expected to be particularly useful when users repeatedly have to sieve through large collections of documents such as those downloaded automatically from the internet. The proposed system takes a whole document collection as input. It first carries out some automatic analysis tasks (named entity recognition, geo-coding, clustering, term extraction), annotates the texts with the generated meta-information and stores the meta-information in a database. The system then generates a zoomable and hyperlinked geographic map enhanced with information on entities and terms found. When the system is used on a regular basis, it builds up a historical database that contains information on which names have been mentioned together with which other names or places, and users can query this database to retrieve information extracted in the past.; Comment: 10 pages

Unsupervised Keyword Extraction from Polish Legal Texts

Jungiewicz, Michał; Łopuszyński, Michał
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
25.83%
In this work, we present an application of the recently proposed unsupervised keyword extraction algorithm RAKE to a corpus of Polish legal texts from the field of public procurement. RAKE is essentially a language and domain independent method. Its only language-specific input is a stoplist containing a set of non-content words. The performance of the method heavily depends on the choice of such a stoplist, which should be domain adopted. Therefore, we complement RAKE algorithm with an automatic approach to selecting non-content words, which is based on the statistical properties of term distribution.

Automatic Taxonomy Extraction from Query Logs with no Additional Sources of Information

Fernandez-Fernandez, Miguel; Gayo-Avello, Daniel
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
35.74%
Search engine logs store detailed information on Web users interactions. Thus, as more and more people use search engines on a daily basis, important trails of users common knowledge are being recorded in those files. Previous research has shown that it is possible to extract concept taxonomies from full text documents, while other scholars have proposed methods to obtain similar queries from query logs. We propose a mixture of both lines of research, that is, mining query logs not to find related queries nor query hierarchies, but actual term taxonomies that could be used to improve search engine effectiveness and efficiency. As a result, in this study we have developed a method that combines lexical heuristics with a supervised classification model to successfully extract hyponymy relations from specialization search patterns revealed from log missions, with no additional sources of information, and in a language independent way.; Comment: 21 pages, 4 figures, 5 tables. Old (2012) unpublished manuscript

L'observatori de terminologia Talaia : mètode i processos

Moré, Joaquim; Rius, Lluís; Vázquez, Mercè; Villarejo, Lluís
Fonte: Universidade Autônoma de Barcelona Publicador: Universidade Autônoma de Barcelona
Tipo: Artigo de Revista Científica Formato: application/pdf
Publicado em //2008 CAT
Relevância na Pesquisa
46%
L’observatori de terminologia Talaia té com a objectiu aplegar unitats neològiques procedents de revistes acadèmiques fent servir eines d’extracció automàtica de terminologia i tècniques de filtratge de tipus lingüístic i estadístic. La combinació de diferents processos permet disposar d’un cabal continu de propostes terminològiques multilingües d’aparició recent en l’àmbit de la societat del coneixement.; El observatorio de terminología Talaia tiene como objetivo recoger unidades neológicas procedentes de revistas académicas utilizando herramientas de extracción automática de terminología y técnicas de filtrado de tipo lingüístico y estadístico. La combinación de diferentes procesos permite disponer de un caudal continuo de propuestas terminológicas multilingües de aparición reciente en el ámbito de la sociedad del conocimiento.; The objective of the Talaia observatory is to collect and organise neological units published in academic journals using linguistic and statistical automatic terminology extraction tools and filtering techniques. The combination of different processes allows for a continual stream of multi-language terminology that has recently appeared in the information society.

Análise do desempenho de extratores automáticos de candidatos a termos: proposta metodológica para tratamento de filtragem dos dados

Teixeira, Rosana de Barros Silva e
Fonte: Universidade de São Paulo. Faculdade de Filosofia, Letras e Ciências Humanas Publicador: Universidade de São Paulo. Faculdade de Filosofia, Letras e Ciências Humanas
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; ; Formato: application/pdf
Publicado em 04/12/2011 POR
Relevância na Pesquisa
26.05%
This article aims to present one aspect of the masters dissertation entitled (Onco)mastology terms: a corpus-mediated approach (2011). This work will explore one of the goals that guided the study, namely, verifying the success rates of four computational tools for automatic extraction of term candidates: Corpógrafo 4.0, WordSmith Tools 3.0, e-Termos and ZExtractor. Two corpora were used in the investigation: the study corpus (MAMAtex), with a total of 563,482 words, and a reference corpus (Banco de Português 1.0), with 125,927,624 words. The first, which is specialized, consists of some of the genres of scientific discourse, of scientific dissemination and instruction in (Onco)mastology, while the second, a generallanguage text, includes various genres. Two approaches were chosen to support this analysis from the theoretical and methodological standpoint: the Communicative Theory of Terminology (CABRÉ 1993) and Corpus Linguistics (SINCLAIR 1991; BERBER SARDINHA 2004, 2005). As revealed by the data, Corpógrafo 4.0 ranks highest, with 27.56% accuracy, followed by ZExtractor (26.05%), WordSmith Tools 3.0 (21.77%) and e-Terms (14.44 %). In order to make feasible the examination of candidates, given that the lists generated by the programs included thousands of words...

Black Magic Meta Data - get a glimpse behind the scene

Vestdam, Thomas; Rasmussen, Henrik Steen; Doornenbal, Marius
Fonte: euroCRIS Publicador: euroCRIS
Tipo: Conference Paper
EN
Relevância na Pesquisa
35.74%
Delivered at the CRIS2014 Conference in Rome; published in Procedia Computer Science 33 (Jul 2014).; Contains conference paper (6 pages) and presentation (16 slides); This paper presents how we utilise natural language processing techniques in order to “automagically” classify information stored in a CRIS, and aggregate the information in a researchers portfolio into a “fingerprint” describing a researchers' research interest. Our approach exploits the fact that entities in a CRIS typically include some kind of text – most notable example being publication abstracts. We explain how the approach can result in automatic detailed classification of information, and argue how we can take advantage of such information in order to facilitate networking. Finally, we describe how we have realised the solution within our CRIS system.

Corpora for computational linguistics; Corpora for computational linguistics

Orasan, Constantin; University of Wolverhampton - United Kingdom; Ha, Le An; Evans, Richard; Hasler, Laura; Mitkov, Ruslan
Fonte: UFSC Publicador: UFSC
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; ; Formato: application/pdf
Publicado em 12/11/2008 POR
Relevância na Pesquisa
26.01%
Since the mid 90s corpora has become very important for computational linguistics. This paper offers a survey of how they are currently used in different fields of the discipline, with particular emphasis on anaphora and coreference resolution, automatic summarisation and term extraction. Their influence on other fields is also briefly discussed.; Since the mid 90s corpora has become very important for computational linguistics. This paper offers a survey of how they are currently used in different fields of the discipline, with particular emphasis on anaphora and coreference resolution, automatic summarisation and term extraction. Their influence on other fields is also briefly discussed.

Linguistically Motivated Negation Processing: An Application for the Detection of Risk Indicators in Unstructured Discharge Summaries

Hagege,Caroline
Fonte: Instituto Politécnico Nacional, Centro de Innovación y Desarrollo Tecnológico en Cómputo Publicador: Instituto Politécnico Nacional, Centro de Innovación y Desarrollo Tecnológico en Cómputo
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/06/2011 EN
Relevância na Pesquisa
25.88%
The paper proposes a linguistically motivated approach to deal with negation in the context of information extraction. This approach is used in a practical application: the automatic detection of cases of hospital acquired infections (HAI) by processing unstructured medical discharge summaries. One of the important processing steps is the extraction of specific terms expressing risk indicators that can lead to the conclusion of HAI cases. This term extraction has to be very accurate and negation has to be taken into account in order to really understand if a string corresponding to a potential risk indicator is attested positively or negatively in the document. We propose a linguistically motivated approach for dealing with negation using both syntactic and semantic information. This approach is first described and then evaluated in the context of our application in the medical domain. The results of evaluation are also compared with other related approaches dealing with negation in medical texts.