S
Sarvnaz Karimi
Researcher at Commonwealth Scientific and Industrial Research Organisation
Publications - 108
Citations - 2318
Sarvnaz Karimi is an academic researcher from Commonwealth Scientific and Industrial Research Organisation. The author has contributed to research in topics: Computer science & Transliteration. The author has an hindex of 22, co-authored 94 publications receiving 1842 citations. Previous affiliations of Sarvnaz Karimi include University of Melbourne & RMIT University.
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Journal ArticleDOI
Cadec: A corpus of adverse drug event annotations
TL;DR: A new rich annotated corpus of medical forum posts on patient-reported Adverse Drug Events (ADEs), which contains text that is largely written in colloquial language and often deviates from formal English grammar and punctuation rules.
Proceedings ArticleDOI
Evaluating topic models for digital libraries
TL;DR: This large-scale user study includes over 70 human subjects evaluating and scoring almost 500 topics learned from collections from a wide range of genres and domains and shows how scoring model -- based on pointwise mutual information of word-pair using Wikipedia, Google and MEDLINE as external data sources - performs well at predicting human scores.
Proceedings ArticleDOI
Location extraction from disaster-related microblogs
TL;DR: This work investigates the feasibility of applying Named Entity Recognizers to extract locations from microblogs, at the level of both geo-location and point-of-interest, and shows that such tools once retrained on microblog data have great potential to detect the where information, even at the granularity of point- of-interest.
Journal ArticleDOI
Text and Data Mining Techniques in Adverse Drug Reaction Detection
TL;DR: In order to highlight the importance of contributions made by computer scientists in this area so far, the existing approaches are categorized and review, and most importantly, areas where more research should be undertaken are identified.
Journal ArticleDOI
Machine transliteration survey
TL;DR: This survey reviews the key methodologies introduced in the transliteration literature and categorizes them based on the resources and algorithms used, and the effectiveness is compared.