SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity
This paper introduces a new task on Multilingual and Cross-lingual SemanticThis paper introduces a new task on Multilingual and Cross-lingual Semantic Word Similarity which measures the semantic similarity of word pairs within and across five languages: English, Farsi, German, Italian and Spanish. High quality datasets were manually curated for the five languages with high inter-annotator agreements (consistently in the 0.9 ballpark). These were used for semi-automatic construction of ten cross-lingual datasets. 17 teams participated in the task, submitting 24 systems in subtask 1 and 14 systems in subtask 2. Results show that systems that combine statistical knowledge from text corpora, in the form of word embeddings, and external knowledge from lexical resources are best performers in both subtasks. More information can be found on the task website: \url{http://alt.qcri.org/semeval2017/task2/}
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Information RetrievalMachine TranslationQuestion AnsweringRepresentation LearningSemantic SimilaritySemantic Textual SimilarityTask 2Text SummarizationWord EmbeddingsWord Sense DisambiguationWord SimilaritySimilar Papers 제목 키워드 기반
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