Transitive probabilistic CLIR models.

Transitive translation could be a useful technique to enlarge the number of supported language pairs for a cross-language information retrieval (CLIR) system in a cost-effective manner. The paper describes several setups for transitive translation based on probabilistic translation models. The transitive CLIR models were evaluated on the CLEF test collection and yielded a retrieval effectiveness\ud up to 83% of monolingual performance, which is significantly better than a baseline using the synonym operator

Morphology in Phonology : introduction

This fourth volume of Catalan Journal of Linguistics is devoted to a topic discussed at length in the literature but which nevertheless remains a challenge for any view of phonology: the morphology-phonology interaction. The papers collected address two related issues, the role of morphological information in phonology and the role of phonological information in morphology. The first six articles (i.e. McCarthy, Wheeler, Downing, van Oostendorp, José and Auger, and Rice) deal with the former topic; the last three (i.e. Bertinetto and Jetchev, Pérez Saldanya and Vallès, and Viaplana), with the latter. Several papers (Wheeler, van Oostendorp, Rice, Bertinetto and Jetchev, Pérez Saldanya and Vallès, and Viaplana) further discuss the role and concept of paradigms, an old Neogrammarian notion to which renewed attention has been payed both from the phonological perspective (cf. work by Benua 1995, 1997; Burzio 1994 and subsequent work; Kenstowicz 1996, 2002; Steriade 2000, and the articles in the recent volume edited by Downing et al. 2005, among others) and from the morphological perspective (cf. work by Aronoff 1994; Bauer 1997, 2001; Carstairs-McCarthy 1994, 1998; Stump 1991, 1997; van Marle 1985, 1994; Wurzel 1989, and several articles in the recent volume edited by Boucher 2002, among others)

FuzzyBIO: a proposal for fuzzy representation of discontinuous entities

Algorithms and the Foundations of Software technolog

Narrative detection in online patient communities

Although narratives on patient forums are a valuable source of medical information, their systematic detection and analysis has so far been limited to a single study. In this study, we examine whether psycho-linguistic features or document embeddings can aid identification of narratives. We also investigate which features distinguish narratives from other social media posts. This study is the rst to automatically identify the topics discussed in narratives on a patient forum. Our results show that for classifying narratives, character 3-grams outperform psycho-linguistic features and document embeddings. We found that narratives are characterized by the use of past tense, health-related words and rst-person pronouns, whereas non-narrative text is associ-ated with the future tense, emotional support words and second-person pronouns. Topic analysis of the patient narratives uncovered fourteen dierent medical topics, ranging from tumor surgery to side eects. Future work will use these methods to extract experiential patient knowledge from social media.Algorithms and the Foundations of Software technolog

Breaking BERT: Understanding its vulnerabilities for biomedical named entity recognition through adversarial attack

Algorithms and the Foundations of Software technolog