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The Discriminating between Similar Languages (DSL) shared task at VarDial challenged participants to build an automatic language identification system to discriminate between 13 languages in 6 groups of highly-similar languages (or national varieties of the same language). In this paper, we describe the submissions made by team UniMelb-NLP, which took part(More)
heterodimers containing a regulatory subunit (see below) and a 110 kDa catalytic subunit (including 110␣ and Department of Signalling The Babraham Institute 110␤) (Hiles et al., 1992; Hu et al., 1993). Both p110␣ and p110␤ are covalently modified and potently inhibited by Cambridge CB2 4AT United Kingdom the fungal metabolite wortmannin contain a §(More)
Language identification is the task of automatically detecting the language(s) present in a document based on the content of the document. In this work, we address the problem of detecting documents that contain text from more than one language (multilingual documents). We introduce a method that is able to detect that a document is multilingual, identify(More)
Online discussion forums are a valuable means for users to resolve specific information needs, both interactively for the participants and statically for users who search/browse over historical thread data. However, the complex structure of forum threads can make it difficult for users to extract relevant information. The discourse structure of web forum(More)
The immunosuppressants rapamycin and FK506 bind to the same intracellular protein, the immunophilin FKBP12. The FKB12-FK506 complex interacts with and inhibits the Ca(2+)-activated protein phosphatase calcineurin. The target of the FKBP12-rapamycin complex has not yet been identified. We report that a protein complex containing 245 kDa and 35 kDa(More)
While various claims have been made about text in social media text being noisy, there has never been a systematic study to investigate just how linguistically noisy or otherwise it is over a range of social media sources. We explore this question empirically over popular social media text types, in the form of YouTube comments, Twitter posts, web user(More)