Resposta contextual automática a mensagens electrónicas

A evolução tecnológica, associada às mudanças sociais a que temos assistido, nomeadamente nas últimas décadas, originou mudanças significativas na forma como os utentes interagem com as instituições, passando a privilegiar a utilização de meios electrónicos, tais como as mensagens de correio electrónico, em detrimento de formas mais tradicionais, como a carta e o telefone. Neste contexto, sendo o ISEP uma instituição de ensino superior que alberga milhares de alunos e recebe centenas de novos alunos todos os anos, necessita de ter condições para que possa responder de forma atempada às inúmeras mensagens de correio electrónico que recebe. Esta necessidade fez com que surgisse um projecto, de nome SiRAC, que servisse para auxiliar na resposta a essas mensagens. O SiRAC tem como objectivo responder a mensagens de correio electrónico de forma automática. De salientar que se admite não ser possível responder a todas as mensagens, privilegiando-se aquelas que são recorrentemente colocadas à Divisão Académica. Assim será possível encurtar o tempo de comunicação entre os diversos intervenientes, criando uma relação mais próxima entre o ISEP e o público que o contacta. O SiRAC analisa as mensagens e procura responder de forma automática sempre que o seu conteúdo possa ser classificado como fazendo parte de um conjunto de questões previamente identificadas pelos recursos humanos da Divisão Académica como recorrentes e para as quais já exista uma resposta tipo. As questões constantes da mensagem são identificadas através de palavras e expressões normalmente associadas aos diferentes tipos de questão. O envio da resposta pressupõe a identificação correcta dos tipos associados e de acordo com requisitos mínimos definidos, de forma a evitar enviar uma resposta errada a uma mensagem. A implementação do SiRAC permite a libertação de recursos humanos da Divisão Académica que anteriormente estavam afectas à resposta de mensagens para o desempenho de outras funções.

Extração de informação de texto formal para a modelação expedita de edifícios monumentais

A extração de informação a partir de descrições textuais para a modelação procedimental de ambientes urbanos é apresentada com solução para os edifícios antigos. No entanto, este tipo de edifício carece de maior cuidado com os detalhes de alto nível. Este artigo descreve uma plataforma para a geração expedita de modelos 3D de edifícios monumentais, cuja arquitetura é modular. O primeiro módulo permite a extração de informação a partir de textos formais, pela integração do NooJ num Web Service. No segundo módulo, toda a informação extraída é mapeada para uma ontologia que define os objetos a contemplar na modelação procedimental, processo esse realizado pelo módulo final que gera os modelos 3D em CityGML, também como um Web Service. A partir desta plataforma, desenvolveu-se um protótipo Web para o caso de estudo da modelação das igrejas da cidade do Porto. Os resultados obtidos deram indicações positivas sobre o modelo de dados definidos e a flexibilidade de representação de estruturas diversificadas, como portas, janelas e outras características de igrejas.

Análise de opiniões expressas nas redes sociais

As redes sociais são cada vez mais utilizadas no nosso dia-a-dia. O recente aumento de popularidade deste tipo de serviço veio trazer novas funcionalidades e aplicações. Os utilizadores contribuem com as suas opiniões e conhecimentos, formando um repositório de informação de grandes proporções. Esta informação é cada vez mais utilizada por empresas, que vêem nas redes sociais uma forma de promover os seus produtos junto do público ou analisar de que forma os mesmos são considerados. O estudo apresentado neste artigo aplicou técnicas de Análise Sentimental para verificar se a informação existente em duas redes sociais (Facebook e Twitter) pode ser utilizada para estimar valores que podem vir a ser obtidos na comercialização de bens ou serviços a serem lançados no mercado.

Extraction automatique d´associations lexicales à partir de corpora

The automatic acquisition of lexical associations from corpora is a crucial issue for Natural Language Processing. A lexical association is a recurrent combination of words that co-occur together more often than expected by chance in a given domain. In fact, lexical associations define linguistic phenomena such as idiomes, collocations or compound words. Due to the fact that the sense of a lexical association is not compositionnal, their identification is fundamental for the realization of analysis and synthesis that take into account all the subtilities of the language. In this report, we introduce a new statistically-based architecture that extracts from naturally occurring texts contiguous and non contiguous. For that purpose, three new concepts have been defined : the positional N-gram models, the Mutual Expectation and the GenLocalMaxs algorithm. Thus, the initial text is fisrtly transformed in a set of positionnal N-grams i.e ordered vectors of simple lexical units. Then, an association measure, the Mutual Expectation, evaluates the degree of cohesion of each positional N-grams based on the identification of local maximum values of Mutual Expectation. Great efforts have also been carried out to evaluate our metodology. For that purpose, we have proposed the normalisation of five well-known association measures and shown that both the Mutual Expectation and the GenLocalMaxs algorithm evidence significant improvements comparing to existent metodologies.

Terminology and knowledge engineering conference. New frontiers in the constructive symbiosis of terminology and knowledge engineering

To meet the increasing demands of the complex inter-organizational processes and the demand for continuous innovation and internationalization, it is evident that new forms of organisation are being adopted, fostering more intensive collaboration processes and sharing of resources, in what can be called collaborative networks (Camarinha-Matos, 2006:03). Information and knowledge are crucial resources in collaborative networks, being their management fundamental processes to optimize. Knowledge organisation and collaboration systems are thus important instruments for the success of collaborative networks of organisations having been researched in the last decade in the areas of computer science, information science, management sciences, terminology and linguistics. Nevertheless, research in this area didn’t give much attention to multilingual contexts of collaboration, which pose specific and challenging problems. It is then clear that access to and representation of knowledge will happen more and more on a multilingual setting which implies the overcoming of difficulties inherent to the presence of multiple languages, through the use of processes like localization of ontologies. Although localization, like other processes that involve multilingualism, is a rather well-developed practice and its methodologies and tools fruitfully employed by the language industry in the development and adaptation of multilingual content, it has not yet been sufficiently explored as an element of support to the development of knowledge representations - in particular ontologies - expressed in more than one language. Multilingual knowledge representation is then an open research area calling for cross-contributions from knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences. This workshop joined researchers interested in multilingual knowledge representation, in a multidisciplinary environment to debate the possibilities of cross-fertilization between knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences applied to contexts where multilingualism continuously creates new and demanding challenges to current knowledge representation methods and techniques. In this workshop six papers dealing with different approaches to multilingual knowledge representation are presented, most of them describing tools, approaches and results obtained in the development of ongoing projects. In the first case, Andrés Domínguez Burgos, Koen Kerremansa and Rita Temmerman present a software module that is part of a workbench for terminological and ontological mining, Termontospider, a wiki crawler that aims at optimally traverse Wikipedia in search of domainspecific texts for extracting terminological and ontological information. The crawler is part of a tool suite for automatically developing multilingual termontological databases, i.e. ontologicallyunderpinned multilingual terminological databases. In this paper the authors describe the basic principles behind the crawler and summarized the research setting in which the tool is currently tested. In the second paper, Fumiko Kano presents a work comparing four feature-based similarity measures derived from cognitive sciences. The purpose of the comparative analysis presented by the author is to verify the potentially most effective model that can be applied for mapping independent ontologies in a culturally influenced domain. For that, datasets based on standardized pre-defined feature dimensions and values, which are obtainable from the UNESCO Institute for Statistics (UIS) have been used for the comparative analysis of the similarity measures. The purpose of the comparison is to verify the similarity measures based on the objectively developed datasets. According to the author the results demonstrate that the Bayesian Model of Generalization provides for the most effective cognitive model for identifying the most similar corresponding concepts existing for a targeted socio-cultural community. In another presentation, Thierry Declerck, Hans-Ulrich Krieger and Dagmar Gromann present an ongoing work and propose an approach to automatic extraction of information from multilingual financial Web resources, to provide candidate terms for building ontology elements or instances of ontology concepts. The authors present a complementary approach to the direct localization/translation of ontology labels, by acquiring terminologies through the access and harvesting of multilingual Web presences of structured information providers in the field of finance, leading to both the detection of candidate terms in various multilingual sources in the financial domain that can be used not only as labels of ontology classes and properties but also for the possible generation of (multilingual) domain ontologies themselves. In the next paper, Manuel Silva, António Lucas Soares and Rute Costa claim that despite the availability of tools, resources and techniques aimed at the construction of ontological artifacts, developing a shared conceptualization of a given reality still raises questions about the principles and methods that support the initial phases of conceptualization. These questions become, according to the authors, more complex when the conceptualization occurs in a multilingual setting. To tackle these issues the authors present a collaborative platform – conceptME - where terminological and knowledge representation processes support domain experts throughout a conceptualization framework, allowing the inclusion of multilingual data as a way to promote knowledge sharing and enhance conceptualization and support a multilingual ontology specification. In another presentation Frieda Steurs and Hendrik J. Kockaert present us TermWise, a large project dealing with legal terminology and phraseology for the Belgian public services, i.e. the translation office of the ministry of justice, a project which aims at developing an advanced tool including expert knowledge in the algorithms that extract specialized language from textual data (legal documents) and whose outcome is a knowledge database including Dutch/French equivalents for legal concepts, enriched with the phraseology related to the terms under discussion. Finally, Deborah Grbac, Luca Losito, Andrea Sada and Paolo Sirito report on the preliminary results of a pilot project currently ongoing at UCSC Central Library, where they propose to adapt to subject librarians, employed in large and multilingual Academic Institutions, the model used by translators working within European Union Institutions. The authors are using User Experience (UX) Analysis in order to provide subject librarians with a visual support, by means of “ontology tables” depicting conceptual linking and connections of words with concepts presented according to their semantic and linguistic meaning. The organizers hope that the selection of papers presented here will be of interest to a broad audience, and will be a starting point for further discussion and cooperation.

Segmentation and Clustering of Textual Sequences: a Typological Approach

The long term goal of this research is to develop a program able to produce an automatic segmentation and categorization of textual sequences into discourse types. In this preliminary contribution, we present the construction of an algorithm which takes a segmented text as input and attempts to produce a categorization of sequences, such as narrative, argumentative, descriptive and so on. Also, this work aims at investigating a possible convergence between the typological approach developed in particular in the field of text and discourse analysis in French by Adam (2008) and Bronckart (1997) and unsupervised statistical learning.

Paraphrasing : scope and typology : a computational approach

This PhD project aims to study paraphrasing, initially understood as the different ways in which the same content is expressed linguistically. We will go into that concept in depth trying to define and delimit its scope more accurately. In that sense, we also aim to discover which kind of structures and phenomena it covers. Although there exist some paraphrasing typologies, the great majority of them only apply to English, and focus on lexical and syntactic transformations. Our intention is to go further into this subject and propose a paraphrasing typology for Spanish and Catalan combining lexical, syntactic, semantic and pragmatic knowledge. We apply a bottom-up methodology trying to collect evidence of this phenomenon from the data. For this purpose, we are initially using the Spanish Wikipedia as our corpus. The internal structure of this encyclopedia makes it a good resource for extracting paraphrasing examples for our investigation. This empirical approach will be complemented with the use of linguistic knowledge, and by comparing and contrasting our results to previously proposed paraphrasing typologies in order to enlarge the possible paraphrasing forms found in our corpus. The fact that the same content can be expressed in many different ways presents a major challenge for Natural Language Processing (NLP) applications. Thus, research on paraphrasing has recently been attracting increasing attention in the fields of NLP and Computational Linguistics. The results obtained in this investigation would be of great interest in many of these applications.

Semàntica del mot : propietats semàntiques de tres verbs de desplaçament

El treball té com a objectiu l'estudi de les propietats semàntiques d'un grup de verbs de desplaçament i els seus corresponents arguments. La informació sobre el tipus de complement que demana cada verb és important de cara a conèixer l'estructura sintàctica de la frase i oferir solucions pràctiques en tasques de Processament del Llenguatge Natural. L'anàlisi se centrarà en els verbs conduir, navegar i volar, a partir dels sentits bàsics que el Diccionari d'ús dels verbs catalans (DUVC) descriu per a cadascun d'aquests verbs i de les seves restriccions selectives. Comprovarem, mitjançant un centenar de frases extretes del Corpus d'Ús del Català a la Web de la Universitat Pompeu Fabra i del Corpus Textual Informatitzat de la Llengua Catalana de l'Institut d'Estudis Catalans, si en la llengua es donen només els sentits i usos descrits en el DUVC i quins són els més freqüents. Finalment, descriurem els noms que fan de nucli dels arguments en termes de trets semàntics.

Estat de la qüestió de l'estudi de l'aspecte lèxic : una proposta cognitiva de classficació d'esdeveniments

Peer-reviewed

A semantic model of selective dissemination of information for digital libraries

In this paper we present the theoretical and methodologicalfoundations for the development of a multi-agentSelective Dissemination of Information (SDI) servicemodel that applies Semantic Web technologies for specializeddigital libraries. These technologies make possibleachieving more efficient information management,improving agent–user communication processes, andfacilitating accurate access to relevant resources. Othertools used are fuzzy linguistic modelling techniques(which make possible easing the interaction betweenusers and system) and natural language processing(NLP) techniques for semiautomatic thesaurus generation.Also, RSS feeds are used as “current awareness bulletins”to generate personalized bibliographic alerts.

Towards the Automatic Merging of Lexical Resources: Automatic Mapping

Lexical Resources are a critical component for Natural Language Processing applications. However, the high cost of comparing and merging different resources has been a bottleneck to have richer resources with a broad range of potential uses for a significant number of languages.With the objective of reducing cost byeliminating human intervention, we present a new method for automating the merging of resources,with special emphasis in what we call the mapping step. This mapping step, which converts the resources into a common format that allows latter the merging, is usually performed with huge manual effort and thus makes the whole process very costly. Thus, we propose a method to perform this mapping fully automatically. To test our method, we have addressed the merging of two verb subcategorization frame lexica for Spanish, The resultsachieved, that almost replicate human work, demonstrate the feasibility of the approach.

A Method Towards the Fully Automatic Merging of Lexical Resources

Lexical Resources are a critical component for Natural Language Processing applications. However, the high cost of comparing and merging different resources has been a bottleneck to obtain richer resources and a broader range of potential uses for a significant number of languages. With the objective of reducing cost by eliminating human intervention, we present a new method towards the automatic merging of resources. This method includes both, the automatic mapping of resources involved to a common format and merging them, once in this format. This paper presents how we have addressed the merging of two verb subcategorization frame lexica for Spanish, but our method will be extended to cover other types of Lexical Resources. The achieved results, that almost replicate human work, demonstrate the feasibility of the approach.

Spotting Translationese in two Corpora of Original and Translated Catalan Texts: an Empirical Approach

This research investigates the phenomenon of translationese in two monolingual comparable corpora of original and translated Catalan texts. Translationese has been defined as the dialect, sub-language or code of translated language. This study aims at giving empirical evidence of translation universals regardless the source language.Traditionally, research conducted on translation strategies has been mainly intuition-based. Computational Linguistics and Natural Language Processing techniques provide reliable information of lexical frequencies, morphological and syntactical distribution in corpora. Therefore, they have been applied to observe which translation strategies occur in these corpora.Results seem to prove the simplification, interference and explicitation hypotheses, whereas no sign of normalization has been detected with the methodology used.The data collected and the resources created for identifying lexical, morphological and syntactic patterns of translations can be useful for Translation Studies teachers, scholars and students: teachers will have more tools to help students avoid the reproduction of translationese patterns. Resources developed will help in detecting non-genuine or inadequate structures in the target language. This fact may imply an improvement in stylistic quality in translations. Translation professionals can also take advantage of these resources to improve their translation quality.

Frame detection over the semantic web

In the past, research in ontology learning from text has mainly focused on entity recognition, taxonomy induction and relation extraction. In this work we approach a challenging research issue: detecting semantic frames from texts and using them to encode web ontologies. We exploit a new generation Natural Language Processing technology for frame detection, and we enrich the frames acquired so far with argument restrictions provided by a super-sense tagger and domain specializations. The results are encoded according to a Linguistic MetaModel, which allows a complete translation of lexical resources and data acquired from text, enabling custom transformations of the enriched frames into modular ontology components.

VIKI : a semiotic-based system for multilingual knowledge retrieval

Abstract Since its creation, the Internet has permeated our daily life. The web is omnipresent for communication, research and organization. This exploitation has resulted in the rapid development of the Internet. Nowadays, the Internet is the biggest container of resources. Information databases such as Wikipedia, Dmoz and the open data available on the net are a great informational potentiality for mankind. The easy and free web access is one of the major feature characterizing the Internet culture. Ten years earlier, the web was completely dominated by English. Today, the web community is no longer only English speaking but it is becoming a genuinely multilingual community. The availability of content is intertwined with the availability of logical organizations (ontologies) for which multilinguality plays a fundamental role. In this work we introduce a very high-level logical organization fully based on semiotic assumptions. We thus present the theoretical foundations as well as the ontology itself, named Linguistic Meta-Model. The most important feature of Linguistic Meta-Model is its ability to support the representation of different knowledge sources developed according to different underlying semiotic theories. This is possible because mast knowledge representation schemata, either formal or informal, can be put into the context of the so-called semiotic triangle. In order to show the main characteristics of Linguistic Meta-Model from a practical paint of view, we developed VIKI (Virtual Intelligence for Knowledge Induction). VIKI is a work-in-progress system aiming at exploiting the Linguistic Meta-Model structure for knowledge expansion. It is a modular system in which each module accomplishes a natural language processing task, from terminology extraction to knowledge retrieval. VIKI is a supporting system to Linguistic Meta-Model and its main task is to give some empirical evidence regarding the use of Linguistic Meta-Model without claiming to be thorough.