Semantic Similarity

The main objective Semantic Similarity is to measure the distance between the semantic meanings of a pair of words, phrases, sentences, or documents. For example, the word “car” is more similar to “bus” than it is to “cat”. The two main approaches to measuring Semantic Similarity are knowledge-based approaches and corpus-based, distributional methods.

Source: Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1176–1200 of 1564 papers

Title	Date	Tasks	Status	Hype
Personalized Ranking in eCommerce Search	Apr 30, 2019	Re-RankingSemantic Similarity	—Unverified	0
Model Comparison for Semantic Grouping	Apr 30, 2019	modelSemantic Similarity	CodeCode Available	0
Supervised Online Hashing via Hadamard Codebook Learning	Apr 28, 2019	RetrievalSemantic Similarity	CodeCode Available	0
Wasserstein-Fisher-Rao Document Distance	Apr 23, 2019	GPUSemantic Similarity	—Unverified	0
Deep Metric Learning Beyond Binary Supervision	Apr 21, 2019	Image CaptioningImage Retrieval	CodeCode Available	0
ERNIE: Enhanced Representation through Knowledge Integration	Apr 19, 2019	Chinese Named Entity RecognitionChinese Sentence Pair Classification	CodeCode Available	3
Inpatient2Vec: Medical Representation Learning for Inpatients	Apr 18, 2019	Representation LearningSemantic Similarity	—Unverified	0
MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations Prediction	Apr 17, 2019	Decision MakingLEMMA	CodeCode Available	0
Gating Mechanisms for Combining Character and Word-level Word Representations: An Empirical Study	Apr 11, 2019	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Word Similarity Datasets for Thai: Construction and Evaluation	Apr 8, 2019	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
LICD: A Language-Independent Approach for Aspect Category Detection	Apr 7, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
A new approach for measuring semantic similarity of ontology concepts using dynamic programming	Apr 4, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning	Apr 4, 2019	ClusteringDeep Hashing	—Unverified	0
Triplet-Based Deep Hashing Network for Cross-Modal Retrieval	Apr 4, 2019	Cross-Modal RetrievalDeep Hashing	—Unverified	0
A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence Representations	Apr 2, 2019	DisentanglementSemantic Similarity	CodeCode Available	0
Import2vec - Learning Embeddings for Software Libraries	Mar 27, 2019	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Learning semantic sentence representations from visually grounded language without lexical knowledge	Mar 27, 2019	Grounded language learningLearning Semantic Representations	CodeCode Available	0
Cross-modal Subspace Learning via Kernel Correlation Maximization and Discriminative Structure Preserving	Mar 26, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
Comparison of State-of-the-Art Deep Learning APIs for Image Multi-Label Classification using Semantic Metrics	Mar 21, 2019	General ClassificationMulti-Label Classification	CodeCode Available	0
Ranked List Loss for Deep Metric Learning	Mar 8, 2019	Image RetrievalMetric Learning	CodeCode Available	0
EL Embeddings: Geometric construction of models for the Description Logic EL ++	Feb 27, 2019	Graph EmbeddingKnowledge Graph Embedding	CodeCode Available	0
Investigating Antigram Behaviour using Distributional Semantics	Jan 15, 2019	Semantic SimilaritySemantic Textual Similarity	—Unverified	0
ParaBank: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-constrained Neural Machine Translation	Jan 11, 2019	DiversityMachine Translation	—Unverified	0
Hierarchy Neighborhood Discriminative Hashing for An Unified View of Single-Label and Multi-Label Image retrieval	Jan 10, 2019	Image RetrievalMulti-Label Image Retrieval	—Unverified	0
Improving Context-Aware Semantic Relationships in Sparse Mobile Datasets	Dec 23, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified	0

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All datasets Annotated corpus for semantic similarity of clinical trial outcomes (expanded corpus)Annotated corpus for semantic similarity of clinical trial outcomes (original corpus)SICK BIOSSES CHIP-STS ClinicalSTS MedSTS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	93.38	—	Unverified
2	SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	91.51	—	Unverified
3	SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	90.69	—	Unverified
4	BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	89.16	—	Unverified
5	BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")	F1	89.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.75	—	Unverified
2	SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.3	—	Unverified
3	SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.3	—	Unverified
4	BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	86.8	—	Unverified
5	BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	84.21	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Doc2VecC	MSE	0.31	—	Unverified
2	LSTM (Tai et al., 2015)	MSE	0.28	—	Unverified
3	Bidirectional LSTM (Tai et al., 2015)	MSE	0.27	—	Unverified
4	combine-skip (Kiros et al., 2015)	MSE	0.27	—	Unverified
5	Dependency Tree-LSTM (Tai et al., 2015)	MSE	0.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BioLinkBERT (large)	Pearson Correlation	0.94	—	Unverified
2	BioLinkBERT (base)	Pearson Correlation	0.93	—	Unverified
3	NCBI_BERT(base) (P+M)	Pearson Correlation	0.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MacBERT-large	Macro F1	85.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CharacterBERT (base, medical, ensemble)	Pearson Correlation	85.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	NCBI_BERT(base) (P+M)	Pearson Correlation	0.85	—	Unverified