Papers Task 2
“Task 2” 태그가 달린 논문 572편 · 필터 해제
Idiom Savant at Semeval-2017 Task 7: Detection and Interpretation of English Puns
This paper describes our system, entitled Idiom Savant, for the 7th Task of the Semeval 2017 workshop, {``}Detection and interpretation of English Puns{''}. Our system consists of two probabilistic models for each type o…
Task 2HCCL at SemEval-2017 Task 2: Combining Multilingual Word Embeddings and Transliteration Model for Semantic Similarity
In this paper, we introduce an approach to combining word embeddings and machine translation for multilingual semantic word similarity, the task2 of SemEval-2017. Thanks to the unsupervised transliteration model, our cro…
Cross-Lingual Word EmbeddingsMachine TranslationMultilingual Word EmbeddingsSemantic Similarity+9Citius at SemEval-2017 Task 2: Cross-Lingual Similarity from Comparable Corpora and Dependency-Based Contexts
This article describes the distributional strategy submitted by the Citius team to the SemEval 2017 Task 2. Even though the team participated in two subtasks, namely monolingual and cross-lingual word similarity, the art…
Task 2Word SimilarityJmp8 at SemEval-2017 Task 2: A simple and general distributional approach to estimate word similarity
We have built a simple corpus-based system to estimate words similarity in multiple languages with a count-based approach. After training on Wikipedia corpora, our system was evaluated on the multilingual subtask of SemE…
Dimensionality ReductionSemantic SimilaritySemantic Textual SimilarityTask 2+1QLUT at SemEval-2017 Task 2: Word Similarity Based on Word Embedding and Knowledge Base
This paper shows the details of our system submissions in the task 2 of SemEval 2017. We take part in the subtask 1 of this task, which is an English monolingual subtask. This task is designed to evaluate the semantic wo…
Task 2Word EmbeddingsWord SimilarityRUFINO at SemEval-2017 Task 2: Cross-lingual lexical similarity by extending PMI and word embeddings systems with a Swadesh's-like list
The RUFINO team proposed a non-supervised, conceptually-simple and low-cost approach for addressing the Multilingual and Cross-lingual Semantic Word Similarity challenge at SemEval 2017. The proposed systems were cross-l…
Semantic Textual SimilarityTask 2Word EmbeddingsWord Sense Disambiguation+1MERALI at SemEval-2017 Task 2 Subtask 1: a Cognitively Inspired approach
In this paper we report on the participation of the MERALI system to the SemEval Task 2 Subtask 1. The MERALI system approaches conceptual similarity through a simple, cognitively inspired, heuristics; it builds on a lin…
Common Sense ReasoningTask 2HHU at SemEval-2017 Task 2: Fast Hash-Based Embeddings for Semantic Word Similarity Assessment
This paper describes the HHU system that participated in Task 2 of SemEval 2017, Multilingual and Cross-lingual Semantic Word Similarity. We introduce our unsupervised embedding learning technique and describe how it was…
Learning Word EmbeddingsSemantic Textual SimilarityTask 2Word Embeddings+1Mahtab at SemEval-2017 Task 2: Combination of Corpus-based and Knowledge-based Methods to Measure Semantic Word Similarity
In this paper, we describe our proposed method for measuring semantic similarity for a given pair of words at SemEval-2017 monolingual semantic word similarity task. We use a combination of knowledge-based and corpus-bas…
Semantic SimilaritySemantic Textual SimilarityTask 2Word SimilaritySew-Embed at SemEval-2017 Task 2: Language-Independent Concept Representations from a Semantically Enriched Wikipedia
This paper describes Sew-Embed, our language-independent approach to multilingual and cross-lingual semantic word similarity as part of the SemEval-2017 Task 2. We leverage the Wikipedia-based concept representations dev…
Semantic Textual SimilarityTask 2Word SimilarityWild Devs' at SemEval-2017 Task 2: Using Neural Networks to Discover Word Similarity
This paper presents Wild Devs{'} participation in the SemEval-2017 Task 2 {``}Multi-lingual and Cross-lingual Semantic Word Similarity{''}, which tries to automatically measure the semantic similarity between two words. …
Multilingual Word EmbeddingsSemantic SimilaritySemantic Textual SimilarityTask 2+2CUNI System for the WMT17 Multimodal Translation Task
In this paper, we describe our submissions to the WMT17 Multimodal Translation Task. For Task 1 (multimodal translation), our best scoring system is a purely textual neural translation of the source image caption to the …
Image CaptioningTask 2TranslationClimbing the Kaggle Leaderboard by Exploiting the Log-Loss Oracle
In the context of data-mining competitions (e.g., Kaggle, KDDCup, ILSVRC Challenge), we show how access to an oracle that reports a contestant's log-loss score on the test set can be exploited to deduce the ground-truth …
Task 2CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages
The CoNLL-SIGMORPHON 2017 shared task on supervised morphological generation required systems to be trained and tested in each of 52 typologically diverse languages. In sub-task 1, submitted systems were asked to predict…
Data AugmentationInductive BiasLEMMATask 2ConceptNet at SemEval-2017 Task 2: Extending Word Embeddings with Multilingual Relational Knowledge
This paper describes Luminoso's participation in SemEval 2017 Task 2, "Multilingual and Cross-lingual Semantic Word Similarity", with a system based on ConceptNet. ConceptNet is an open, multilingual knowledge graph that…
General KnowledgeMultilingual Word EmbeddingsTask 2Word Embeddings+1Skin Lesion Analysis Towards Melanoma Detection Using Deep Learning Network
Skin lesion is a severe disease in world-wide extent. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due…
Deep LearningGeneral ClassificationLesion ClassificationLesion Segmentation+1JU_KS_Group@FIRE 2016: Consumer Health Information Search
In this paper, we describe the methodology used and the results obtained by us for completing the tasks given under the shared task on Consumer Health Information Search (CHIS) collocated with the Forum for Information R…
Information RetrievalRetrievalTask 2DeepNNNER: Applying BLSTM-CNNs and Extended Lexicons to Named Entity Recognition in Tweets
In this paper, we describe the DeepNNNER entry to The 2nd Workshop on Noisy User-generated Text (WNUT) Shared Task {\#}2: Named Entity Recognition in Twitter. Our shared task submission adopts the bidirectional LSTM-CNN …
DiversityFeature Engineeringnamed-entity-recognitionNamed Entity Recognition+4The GW/LT3 VarDial 2016 Shared Task System for Dialects and Similar Languages Detection
This paper describes the GW/LT3 contribution to the 2016 VarDial shared task on the identification of similar languages (task 1) and Arabic dialects (task 2). For both tasks, we experimented with Logistic Regression and …
Feature EngineeringregressionTask 2ASIREM Participation at the Discriminating Similar Languages Shared Task 2016
This paper presents the system built by ASIREM team for the Discriminating between Similar Languages (DSL) Shared task 2016. It describes the system which uses character-based and word-based n-grams separately. ASIREM pa…
Dialect IdentificationLanguage IdentificationTask 2