This paper describes the SNAP system, which participated in Task 4 of SemEval-2014: Aspect Based Sentiment Analysis. We use an XML-based pipeline that combines several independent components to perform each subtask. Key resources used by the system are Bing Liu's sentiment lexicon, Stanford CoreNLP, RFTagger, several machine learning algorithms and WordNet. SNAP achieved satisfactory results in the evaluation, placing in the top half of the field for most subtasks.

The Autumn School for Information Retrieval and Information Foraging (ASIRF) 2019 took place at Schloss Dagstuhl in Germany from September 22nd to 27th. The event featured eight lectures and tutorials from information retrieval experts and stood out due to the diversity of the participants, both regarding their cultural background and research. A varied social program complemented the scientific exchange.

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