An Empirical Approach to Temporal Reference Resolution

This paper presents the results of an empirical investigation of temporal reference resolution in scheduling dialogs. The algorithm adopted is primarily a linear-recency based approach that does not include a model of global focus. A fully automatic system has been developed and evaluated on unseen test data with good results. This paper presents the results of an intercoder reliability study, a model of temporal reference resolution that supports linear recency and has very good coverage, the results of the system evaluated on unseen test data, and a detailed analysis of the dialogs assessing the viability of the approach.Comment: 13 pages, latex using aclap.st

Emotions in context: examining pervasive affective sensing systems, applications, and analyses

Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; “sensing”, “analysis”, and “application”. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing

Metaphor in Analytic Philosophy and Cognitive Science

This article surveys theories of metaphor in analytic philosophy and cognitive science. In particular, it focuses on contemporary semantic, pragmatic and non-cognitivist theories of linguistic metaphor and on the Conceptual Metaphor Theory advanced by George Lakoff and his school. Special attention is given to the mechanisms that are shared by nearly all these approaches, i.e. mechanisms of interaction and mapping between conceptual domains. Finally, the article discusses several recent attempts to combine these theories of linguistic and conceptual metaphor into a unitary account

Neogeography: The Challenge of Channelling Large and Ill-Behaved Data Streams

Neogeography is the combination of user generated data and experiences with mapping technologies. In this article we present a research project to extract valuable structured information with a geographic component from unstructured user generated text in wikis, forums, or SMSes. The extracted information should be integrated together to form a collective knowledge about certain domain. This structured information can be used further to help users from the same domain who want to get information using simple question answering system. The project intends to help workers communities in developing countries to share their knowledge, providing a simple and cheap way to contribute and get benefit using the available communication technology

Spectators’ aesthetic experiences of sound and movement in dance performance

In this paper we present a study of spectators’ aesthetic experiences of sound and movement in live dance performance. A multidisciplinary team comprising a choreographer, neuroscientists and qualitative researchers investigated the effects of different sound scores on dance spectators. What would be the impact of auditory stimulation on kinesthetic experience and/or aesthetic appreciation of the dance? What would be the effect of removing music altogether, so that spectators watched dance while hearing only the performers’ breathing and footfalls? We investigated audience experience through qualitative research, using post-performance focus groups, while a separately conducted functional brain imaging (fMRI) study measured the synchrony in brain activity across spectators when they watched dance with sound or breathing only. When audiences watched dance accompanied by music the fMRI data revealed evidence of greater intersubject synchronisation in a brain region consistent with complex auditory processing. The audience research found that some spectators derived pleasure from finding convergences between two complex stimuli (dance and music). The removal of music and the resulting audibility of the performers’ breathing had a significant impact on spectators’ aesthetic experience. The fMRI analysis showed increased synchronisation among observers, suggesting greater influence of the body when interpreting the dance stimuli. The audience research found evidence of similar corporeally focused experience. The paper discusses possible connections between the findings of our different approaches, and considers the implications of this study for interdisciplinary research collaborations between arts and sciences

The biomedical discourse relation bank

<p>Abstract</p> <p>Background</p> <p>Identification of discourse relations, such as causal and contrastive relations, between situations mentioned in text is an important task for biomedical text-mining. A biomedical text corpus annotated with discourse relations would be very useful for developing and evaluating methods for biomedical discourse processing. However, little effort has been made to develop such an annotated resource.</p> <p>Results</p> <p>We have developed the Biomedical Discourse Relation Bank (BioDRB), in which we have annotated explicit and implicit discourse relations in 24 open-access full-text biomedical articles from the GENIA corpus. Guidelines for the annotation were adapted from the Penn Discourse TreeBank (PDTB), which has discourse relations annotated over open-domain news articles. We introduced new conventions and modifications to the sense classification. We report reliable inter-annotator agreement of over 80% for all sub-tasks. Experiments for identifying the sense of explicit discourse connectives show the connective itself as a highly reliable indicator for coarse sense classification (accuracy 90.9% and F1 score 0.89). These results are comparable to results obtained with the same classifier on the PDTB data. With more refined sense classification, there is degradation in performance (accuracy 69.2% and F1 score 0.28), mainly due to sparsity in the data. The size of the corpus was found to be sufficient for identifying the sense of explicit connectives, with classifier performance stabilizing at about 1900 training instances. Finally, the classifier performs poorly when trained on PDTB and tested on BioDRB (accuracy 54.5% and F1 score 0.57).</p> <p>Conclusion</p> <p>Our work shows that discourse relations can be reliably annotated in biomedical text. Coarse sense disambiguation of explicit connectives can be done with high reliability by using just the connective as a feature, but more refined sense classification requires either richer features or more annotated data. The poor performance of a classifier trained in the open domain and tested in the biomedical domain suggests significant differences in the semantic usage of connectives across these domains, and provides robust evidence for a biomedical sublanguage for discourse and the need to develop a specialized biomedical discourse annotated corpus. The results of our cross-domain experiments are consistent with related work on identifying connectives in BioDRB.</p

"Confortation": About a New Category for Analyzing Biomedical Texts

International audienceIn this paper we present a new approach to the expression of certainty and uncertainty in scientific experimental articles. This will permit to ascertain the validity of knowledge extracted from biological literature and used to automatically populate a domain ontology. We argue that lexical terms such as show, find, observe... express a semantic category different from the one characterized by markers such as demonstrate, validate, support... We name the latter category “confortation” as it conveys a notion of strengthening and we propose five other semantic categories: lack of knowledge, objects of study, hypothesis, observations, and general knowledge. This last category and the linguistic phenomenon of reported speech are respectively examined as consensual truth and as knowledge reported from identified scientific sources

Exploring figurative language recognition: a comprehensive study of human and machine approaches

Treballs Finals de Grau de Llengües i Literatures Modernes. Facultat de Filologia. Universitat de Barcelona. Curs: 2022-2023. Tutora: Elisabet Comelles Pujadas[eng] Figurative language (FL) plays a significant role in human communication. Understanding and interpreting FL is essential for humans to fully grasp the intended message, appreciate cultural nuances, and engage in effective interaction. For machines, comprehending FL presents a challenge due to its complexity and ambiguity. Enabling machines to understand FL has become increasingly important in sentiment analysis, text classification, and social media monitoring, for instance, benefits from accurately recognizing figurative expressions to capture subtle emotions and extract meaningful insights. Machine translation also requires the ability to accurately convey FL to ensure translations reflect the intended meaning and cultural nuances. Therefore, developing computational methods to enable machines to understand and interpret FL is crucial. By bridging the gap between human and machine understanding of FL, we can enhance communication, improve language-based applications, and unlock new possibilities in human-machine interactions. Keywords: figurative language, NLP, human-machine communication.[cat] El Llenguatge Figuratiu (LF) té un paper important en la comunicació humana. Per entendre completament els missatges, apreciar els matisos culturals i la interacció efectiva, és necessària la capacitat d'interpretar el LF. No obstant això, els ordinadors tenen dificultats per entendre la LF a causa de la seva complexitat i ambigüitat. És crític que els ordinadors siguin capaços de reconèixer el LF, especialment en àrees com l'anàlisi de sentiments, la classificació de textos i la supervisió de les xarxes socials. El reconeixement precís del LF permet capturar emocions i extreure idees semàntiques. La traducció automàtica també requereix una representació precisa del LF per reflectir el significat previst i els matisos culturals. Per tant, és rellevant desenvolupar mètodes computacionals que ajudin els ordinadors a comprendre i interpretar el LF. Fer un pont entre la comprensió humana i màquina del LF pot millorar la comunicació, desenvolupar aplicacions de llenguatge i obrir noves possibilitats per a la interacció home-màquina. Paraules clau: llenguatge figuratiu, processament del llenguatge natural, interacció home-màquina