pwc-archive/papers-with-abstracts huggingface dataset:
Using Wikipedia to Validate the Terminology found in a Corpus of Basic Textbooks
Authors: Jorge Vivaldi, Luis Adri{\'a}n Cabrera-Diego, Gerardo Sierra, Mar{\'\i}a Pozzi
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Translation

A scientific vocabulary is a set of terms that designate scientific concepts. This set of lexical units can be used in several applications ranging from the development of terminological dictionaries and machine translation systems to the development of lexical databases and beyond. Even though automatic term recognition systems exist since the 80s, this process is still mainly done by hand, since it generally yields more accurate results, although not in less time and at a higher cost. Some of the reasons for this are the fairly low precision and recall results obtained, the domain dependence of existing tools and the lack of available semantic knowledge needed to validate these results. In this paper we present a method that uses Wikipedia as a semantic knowledge resource, to validate term candidates from a set of scientific text books used in the last three years of high school for mathematics, health education and ecology. The proposed method may be applied to any domain or language (assuming there is a minimal coverage by Wikipedia).
The SERENOA Project: Multidimensional Context-Aware Adaptation of Service Front-Ends
Authors: Javier Caminero, Mari Carmen Rodr{\'\i}guez, V, Jean erdonckt, Fabio Patern{\`o}, Joerg Rett, Dave Raggett, Jean-Loup Comeliau, Ignacio Mar{\'\i}n
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The SERENOA project is aimed at developing a novel, open platform for enabling the creation of context-sensitive Service Front-Ends (SFEs). A context-sensitive SFE provides a user interface (UI) that allows users to interact with remote services, and which exhibits some capability to be aware of the context and to react to changes of this context in a continuous way. As a result, such UI will be adapted to e.g. a person's devices, tasks, preferences, abilities, and social relationships, as well as the conditions of the surrounding physical environment, thus improving people's satisfaction and performance compared to traditional SFEs based on manually designed UIs. The final aim is to support humans in a more effective, personalized and consistent way, thus improving the quality of life for citizens. In this scenario, we envisage SERENOA as the reference implementation of a SFE adaptation platform for the 'Future Internet'.
French and German Corpora for Audience-based Text Type Classification
Authors: Amalia Todirascu, Sebastian Pad{\'o}, Jennifer Krisch, Max Kisselew, Ulrich Heid
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Dependency Parsing, General Classification, Text Categorization, Text Classification, Text Simplification, Vocal Bursts Type Prediction

This paper presents some of the results of the CLASSYN project which investigated the classification of text according to audience-related text types. We describe the design principles and the properties of the French and German linguistically annotated corpora that we have created. We report on tools used to collect the data and on the quality of the syntactic annotation. The CLASSYN corpora comprise two text collections to investigate general text types difference between scientific and popular science text on the two domains of medical and computer science.
The IULA Treebank
Authors: Montserrat Marimon, Beatriz Fisas, N{\'u}ria Bel, Jorge Vivaldi, Sergi Torner, Merc{\`e} Lorente, Silvia V{\'a}zquez, Marta Villegas
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: POS

This paper describes on-going work for the construction of a new treebank for Spanish, The IULA Treebank. This new resource will contain about 60,000 richly annotated sentences as an extension of the already existing IULA Technical Corpus which is only PoS tagged. In this paper we have focused on describing the work done for defining the annotation process and the treebank design principles. We report on how the used framework, the DELPH-IN processing framework, has been crucial in the design principles and in the bootstrapping strategy followed, especially in what refers to the use of stochastic modules for reducing parsing overgeneration. We also report on the different evaluation experiments carried out to guarantee the quality of the already available results.
Modality in Text: a Proposal for Corpus Annotation
Authors: Iris Hendrickx, Am{\'a}lia Mendes, Silvia Mencarelli
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Opinion Mining, Sentence, Sentiment Analysis

We present a annotation scheme for modality in Portuguese. In our annotation scheme we have tried to combine a more theoretical linguistic viewpoint with a practical annotation scheme that will also be useful for NLP research but is not geared towards one specific application. Our notion of modality focuses on the attitude and opinion of the speaker, or of the subject of the sentence. We validated the annotation scheme on a corpus sample of approximately 2000 sentences that we fully annotated with modal information using the MMAX2 annotation tool to produce XML annotation. We discuss our main findings and give attention to the difficult cases that we encountered as they illustrate the complexity of modality and its interactions with other elements in the text.
Rule-based Entity Recognition and Coverage of SNOMED CT in Swedish Clinical Text
Authors: Maria Skeppstedt, Maria Kvist, Hercules Dalianis
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: named-entity-recognition, Named Entity Recognition, Named Entity Recognition (NER)

Named entity recognition of the clinical entities disorders, findings and body structures is needed for information extraction from unstructured text in health records. Clinical notes from a Swedish emergency unit were annotated and used for evaluating a rule- and terminology-based entity recognition system. This system used different preprocessing techniques for matching terms to SNOMED CT, and, one by one, four other terminologies were added. For the class body structure, the results improved with preprocessing, whereas only small improvements were shown for the classes disorder and finding. The best average results were achieved when all terminologies were used together. The entity body structure was recognised with a precision of 0.74 and a recall of 0.80, whereas lower results were achieved for disorder (precision: 0.75, recall: 0.55) and for finding (precision: 0.57, recall: 0.30). The proportion of entities containing abbreviations were higher for false negatives than for correctly recognised entities, and no entities containing more than two tokens were recognised by the system. Low recall for disorders and findings shows both that additional methods are needed for entity recognition and that there are many expressions in clinical text that are not included in SNOMED CT.
An Evaluation of the Effect of Automatic Preprocessing on Syntactic Parsing for Biomedical Relation Extraction
Authors: Md. Faisal Mahbub Chowdhury, Alberto Lavelli
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Part-Of-Speech Tagging, Relation, Relation Extraction

Relation extraction (RE) is an important text mining task which is the basis for further complex and advanced tasks. In state-of-the-art RE approaches, syntactic information obtained through parsing plays a crucial role. In the context of biomedical RE previous studies report usage of various automatic preprocessing techniques applied before parsing the input text. However, these studies do not specify to what extent such techniques improve RE results and to what extent they are corpus specific as well as parser specific. In this paper, we aim at addressing these issues by using various preprocessing techniques, two syntactic tree kernel based RE approaches and two different parsers on 5 widely used benchmark biomedical corpora of the protein-protein interaction (PPI) extraction task. We also provide analyses of various corpus characteristics to verify whether there are correlations between these characteristics and the RE results obtained. These analyses of corpus characteristics can be exploited to compare the 5 PPI corpora.
Federated Search: Towards a Common Search Infrastructure
Authors: Herman Stehouwer, Matej Durco, Eric Auer, Daan Broeder
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Language Acquisition

Within scientific institutes there exist many language resources. These resources are often quite specialized and relatively unknown. The current infrastructural initiatives try to tackle this issue by collecting metadata about the resources and establishing centers with stable repositories to ensure the availability of the resources. It would be beneficial if the researcher could, by means of a simple query, determine which resources and which centers contain information useful to his or her research, or even work on a set of distributed resources as a virtual corpus. In this article we propose an architecture for a distributed search environment allowing researchers to perform searches in a set of distributed language resources.
Evaluating and improving syntactic lexica by plugging them within a parser
Authors: Elsa Tolone, Beno{\^\i}t Sagot, {\'E}ric Villemonte de la Clergerie
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: TAG

We present some evaluation results for four French syntactic lexica, obtained through their conversion to the Alexina format used by the Lefff lexicon, and their integration within the large-coverage TAG-based FRMG parser. The evaluations are run on two test corpora, annotated with two distinct annotation formats, namely EASy/Passage chunks and relations and CoNLL dependencies. The information provided by the evaluation results provide valuable feedback about the four lexica. Moreover, when coupled with error mining techniques, they allow us to identify how these lexica might be improved.
The Herme Database of Spontaneous Multimodal Human-Robot Dialogues
Authors: Jing Guang Han, Emer Gilmartin, Celine De Looze, Brian Vaughan, Nick Campbell
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Gesture Recognition, Speech Recognition, Speech Synthesis

This paper presents methodologies and tools for language resource (LR) construction. It describes a database of interactive speech collected over a three-month period at the Science Gallery in Dublin, where visitors could take part in a conversation with a robot. The system collected samples of informal, chatty dialogue -- normally difficult to capture under laboratory conditions for human-human dialogue, and particularly so for human-machine interaction. The conversations were based on a script followed by the robot consisting largely of social chat with some task-based elements. The interactions were audio-visually recorded using several cameras together with microphones. As part of the conversation the participants were asked to sign a consent form giving permission to use their data for human-machine interaction research. The multimodal corpus will be made available to interested researchers and the technology developed during the three-month exhibition is being extended for use in education and assisted-living applications.
Source-Language Dictionaries Help Non-Expert Users to Enlarge Target-Language Dictionaries for Machine Translation
Authors: V{\'\i}ctor M. S{\'a}nchez-Cartagena, Miquel Espl{\`a}-Gomis, Juan Antonio P{\'e}rez-Ortiz
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Translation

In this paper, a previous work on the enlargement of monolingual dictionaries of rule-based machine translation systems by non-expert users is extended to tackle the complete task of adding both source-language and target-language words to the monolingual dictionaries and the bilingual dictionary. In the original method, users validate whether some suffix variations of the word to be inserted are correct in order to find the most appropriate inflection paradigm. This method is now improved by taking advantage from the strong correlation detected between paradigms in both languages to reduce the search space of the target-language paradigm once the source-language paradigm is known. Results show that, when the source-language word has already been inserted, the system is able to more accurately predict which is the right target-language paradigm, and the number of queries posed to users is significantly reduced. Experiments also show that, when the source language and the target language are not closely related, it is only the source-language part-of-speech category, but not the rest of information provided by the source-language paradigm, which helps to correctly classify the target-language word.
EXMARaLDA and the FOLK tools --- two toolsets for transcribing and annotating spoken language
Authors: Thomas Schmidt
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper presents two toolsets for transcribing and annotating spoken language: the EXMARaLDA system, developed at the University of Hamburg, and the FOLK tools, developed at the Institute for the German Language in Mannheim. Both systems are targeted at users interested in the analysis of spontaneous, multi-party discourse. Their main user community is situated in conversation analysis, pragmatics, sociolinguistics and related fields. The paper gives an overview of the individual tools of the two systems â€• the Partitur-Editor, a tool for multi-level annotation of audio or video recordings, the Corpus Manager, a tool for creating and administering corpus metadata, EXAKT, a query and analysis tool for spoken language corpora, FOLKER, a transcription editor optimized for speed and efficiency of transcription, and OrthoNormal, a tool for orthographical normalization of transcription data. It concludes with some thoughts about the integration of these tools into the larger tool landscape.
ISO 24617-2: A semantically-based standard for dialogue annotation
Authors: Harry Bunt, Alex, Jan ersson, Jae-Woong Choe, Alex Chengyu Fang, Koiti Hasida, Volha Petukhova, Andrei Popescu-Belis, David Traum
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper summarizes the latest, final version of ISO standard 24617-2 ``Semantic annotation framework, Part 2: Dialogue acts''''''''. Compared to the preliminary version ISO DIS 24617-2:2010, described in Bunt et al. (2010), the final version additionally includes concepts for annotating rhetorical relations between dialogue units, defines a full-blown compositional semantics for the Dialogue Act Markup Language DiAML (resulting, as a side-effect, in a different treatment of functional dependence relations among dialogue acts and feedback dependence relations); and specifies an optimally transparent XML-based reference format for the representation of DiAML annotations, based on the systematic application of the notion of `ideal concrete syntax'. We describe these differences and briefly discuss the design and implementation of an incremental method for dialogue act recognition, which proves the usability of the ISO standard for automatic dialogue annotation.
Towards a methodology for automatic identification of hypernyms in the definitions of large-scale dictionary
Authors: Inga Gheorghita, Jean-Marie Pierrel
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Retrieval

The purpose of this paper is to identify automatically hypernyms for dictionary entries by exploring their definitions. In order to do this, we propose a weighting methodology that lets us assign to each lexeme a weight in a definition. This fact allows us to predict that lexemes with the highest weight are the closest hypernyms of the defined lexeme in the dictionary. The extracted semantic relation is-a is used for the automatic construction of a thesaurus for image indexing and retrieval. We conclude the paper by showing some experimental results to validate our method and by presenting our methodology of automatic thesaurus construction.
A review corpus annotated for negation, speculation and their scope
Authors: Natalia Konstantinova, Sheila C.M. de Sousa, Noa P. Cruz, Manuel J. Ma{\~n}a, Maite Taboada, Ruslan Mitkov
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Natural Language Inference, Negation, Negation Detection, Opinion Mining, Sentence, Sentiment Analysis

This paper presents a freely available resource for research on handling negation and speculation in review texts. The SFU Review Corpus, consisting of 400 documents of movie, book, and consumer product reviews, was annotated at the token level with negative and speculative keywords and at the sentence level with their linguistic scope. We report statistics on corpus size and the consistency of annotations. The annotated corpus will be useful in many applications, such as document mining and sentiment analysis.
Developing a large semantically annotated corpus
Authors: Valerio Basile, Johan Bos, Kilian Evang, Noortje Venhuizen
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Boundary Detection, Part-Of-Speech Tagging

What would be a good method to provide a large collection of semantically annotated texts with formal, deep semantics rather than shallow? We argue that a bootstrapping approach comprising state-of-the-art NLP tools for parsing and semantic interpretation, in combination with a wiki-like interface for collaborative annotation of experts, and a game with a purpose for crowdsourcing, are the starting ingredients for fulfilling this enterprise. The result is a semantic resource that anyone can edit and that integrates various phenomena, including predicate-argument structure, scope, tense, thematic roles, rhetorical relations and presuppositions, into a single semantic formalism: Discourse Representation Theory. Taking texts rather than sentences as the units of annotation results in deep semantic representations that incorporate discourse structure and dependencies. To manage the various (possibly conflicting) annotations provided by experts and non-experts, we introduce a method that stores ``Bits of Wisdom'' in a database as stand-off annotations.
Dynamic web service deployment in a cloud environment
Authors: Marc Kemps-Snijders, Matthijs Brouwer, Jan Pieter Kunst, Tom Visser
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Semantic Role Labeling, Speech Recognition

E-infrastructure projects such as CLARIN do not only make research data available to the scientific community, but also deliver a growing number of web services. While the standard methods for deploying web services using dedicated (virtual) server may suffice in many circumstances, CLARIN centers are also faced with a growing number of services that are not frequently used and for which significant compute power needs to be reserved. This paper describes an alternative approach towards service deployment capable of delivering on demand services in a workflow using cloud infrastructure capabilities. Services are stored as disk images and deployed on a workflow scenario only when needed this helping to reduce the overall service footprint.
Associative and Semantic Features Extracted From Web-Harvested Corpora
Authors: Elias Iosif, Maria Giannoudaki, Eric Fosler-Lussier, Alex Potamianos, ros
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Classification, General Classification, Information Retrieval, Language Modelling, Semantic Role Labeling, Semantic Textual Similarity, Spoken Dialogue Systems

We address the problem of automatic classification of associative and semantic relations between words, and particularly those that hold between nouns. Lexical relations such as synonymy, hypernymy/hyponymy, constitute the fundamental types of semantic relations. Associative relations are harder to define, since they include a long list of diverse relations, e.g., ''''''``Cause-Effect'''''''', ''''''``Instrument-Agency''''''''. Motivated by findings from the literature of psycholinguistics and corpus linguistics, we propose features that take advantage of general linguistic properties. For evaluation we merged three datasets assembled and validated by cognitive scientists. A proposed priming coefficient that measures the degree of asymmetry in the order of appearance of the words in text achieves the best classification results, followed by context-based similarity metrics. The web-based features achieve classification accuracy that exceeds 85{\%}.
Collection of a corpus of Dutch SMS
Authors: Maaske Treurniet, Orph{\'e}e De Clercq, Henk van den Heuvel, Nelleke Oostdijk
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper we present the first freely available corpus of Dutch text messages containing data originating from the Netherlands and Flanders. This corpus has been collected in the framework of the SoNaR project and constitutes a viable part of this 500-million-word corpus. About 53,000 text messages were collected on a large scale, based on voluntary donations. These messages will be distributed as such. In this paper we focus on the data collection processes involved and after studying the effect of media coverage we show that especially free publicity in newspapers and on social media networks results in more contributions. All SMS are provided with metadata information. Looking at the composition of the corpus, it becomes visible that a small number of people have contributed a large amount of data, in total 272 people have contributed to the corpus during three months. The number of women contributing to the corpus is larger than the number of men, but male contributors submitted larger amounts of data. This corpus will be of paramount importance for sociolinguistic research and normalisation studies.
Evaluating Hebbian Self-Organizing Memories for Lexical Representation and Access
Authors: Claudia Marzi, Marcello Ferro, Claudia Caudai, Vito Pirrelli
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Time Series Analysis

The lexicon is the store of words in long-term memory. Any attempt at modelling lexical competence must take issues of string storage seriously. In the present contribution, we discuss a few desiderata that any biologically-inspired computational model of the mental lexicon has to meet, and detail a multi-task evaluation protocol for their assessment. The proposed protocol is applied to a novel computational architecture for lexical storage and acquisition, the ''''''``Topological Temporal Hebbian SOMs'''''''' (T2HSOMs), which are grids of topologically organised memory nodes with dedicated sensitivity to time-bound sequences of letters. These maps can provide a rigorous and testable conceptual framework within which to provide a comprehensive, multi-task protocol for testing the performance of Hebbian self-organising memories, and a comprehensive picture of the complex dynamics between lexical processing and the acquisition of morphological structure.
A Corpus for a Gesture-Controlled Mobile Spoken Dialogue System
Authors: Nikos Tsourakis, Manny Rayner
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Speech Recognition, Spoken Dialogue Systems

Speech and hand gestures offer the most natural modalities for everyday human-to-human interaction. The availability of diverse spoken dialogue applications and the proliferation of accelerometers on consumer electronics allow the introduction of new interaction paradigms based on speech and gestures. Little attention has been paid however to the manipulation of spoken dialogue systems through gestures. Situation-induced disabilities or real disabilities are determinant factors that motivate this type of interaction. In this paper we propose six concise and intuitively meaningful gestures that can be used to trigger the commands in any SDS. Using different machine learning techniques we achieve a classification error for the gesture patterns of less than 5{\%}, and we also compare our own set of gestures to ones proposed by users. Finally, we examine the social acceptability of the specific interaction scheme and encounter high levels of acceptance for public use.