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Found 23 papers, 2 papers with code
FAST: A carefully sampled and cognitively motivated dataset for distributional semantic evaluation
What is the first word that comes to your mind when you hear giraffe, or damsel, or freedom?
How Will Your Tweet Be Received? Predicting the Sentiment Polarity of Tweet Replies
As a strong baseline, we propose a two-stage DL-based method: first, we create automatically labeled training data by applying a standard sentiment classifier to tweet replies and aggregating its predictions for each original tweet; our rationale is that individual errors made by the classifier are likely to cancel out in the aggregation step.
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Tweet-Reply Sentiment Analysis
on RETWEET
Corpus Query Lingua Franca part II: Ontology
The present paper outlines the projected second part of the Corpus Query Lingua Franca (CQLF) family of standards: CQLF Ontology, which is currently in the process of standardization at the International Standards Organization (ISO), in its Technical Committee 37, Subcommittee 4 (TC37SC4) and its national mirrors.
EmpiriST Corpus 2.0: Adding Manual Normalization, Lemmatization and Semantic Tagging to a German Web and CMC Corpus
The EmpiriST corpus (Bei{\ss}wenger et al., 2016) is a manually tokenized and part-of-speech tagged corpus of approximately 23, 000 tokens of German Web and CMC (computer-mediated communication) data.
EmotiKLUE at IEST 2018: Topic-Informed Classification of Implicit Emotions
EmotiKLUE is a submission to the Implicit Emotion Shared Task.
Large-scale evaluation of dependency-based DSMs: Are they worth the effort?
This paper presents a large-scale evaluation study of dependency-based distributional semantic models.
CogALex-V Shared Task: Mach5 -- A traditional DSM approach to semantic relatedness
This contribution provides a strong baseline result for the CogALex-V shared task using a traditional {``}count{''}-type DSM (placed in rank 2 out of 7 in subtask 1 and rank 3 out of 6 in subtask 2).
The CogALex-V Shared Task on the Corpus-Based Identification of Semantic Relations
The task is split into two subtasks: (i) identification of related word pairs vs. unrelated ones; (ii) classification of the word pairs according to their semantic relation.
A Large Scale Evaluation of Distributional Semantic Models: Parameters, Interactions and Model Selection
This paper presents the results of a large-scale evaluation study of window-based Distributional Semantic Models on a wide variety of tasks.
