A Generic NLI approach for Classification of Sentiment Associated with Therapies

This paper describes our system for addressing SMM4H 2023 Shared Task 2 on "Classification of sentiment associated with therapies (aspect-oriented)". In our work, we adopt an approach based on Natural language inference (NLI) to formulate this task as a sentence pair classification problem, and train transformer models to predict sentiment associated with a therapy on a given text. Our best model achieved 75.22\% F1-score which was 11\% (4\%) more than the mean (median) score of all teams' submissions.Comment: Accepted in Workshop on Social Media Mining for Health 2023 (#SMM4H

Workshop on Semantic Data Management: A Summary Report

The International Workshop on Semantic Data Management (SemData) was held in Singapore co-located with the VLDB Conference 2010, with the goal of serving as a platform for the discussion and investigation of various aspects related to semantic databases and data management in the large. The workshop was a full-day event featuring two research sessions, one industry session and a panel discussion, and attracted over 25 attendees. This report summarizes the key topics presented, interesting ideas discussed and the new perspectives identified during the workshop.(1

Towards ontology-driven navigation of the lipid bibliosphere

10.1186/1471-2105-9-S1-S5BMC Bioinformatics9SUPPL. 1BBMI

Discovery of transcription factor binding sites through integration of generic motif

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