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

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Showing 1476–1500 of 1564 papers

Title	Date	Tasks	Status
SemEval-2015 Task 1: Paraphrase and Semantic Similarity in Twitter (PIT)	Jun 1, 2015	Information RetrievalParaphrase Identification	—Unverified
UMDuluth-BlueTeam: SVCSTS - A Multilingual and Chunk Level Semantic Similarity System	Jun 1, 2015	Semantic SimilaritySemantic Textual Similarity	—Unverified
Multilinguality at Your Fingertips : BabelNet, Babelfy and Beyond !	Jun 1, 2015	Entity LinkingSemantic Similarity	—Unverified
RTM-DCU: Predicting Semantic Similarity with Referential Translation Machines	Jun 1, 2015	Machine TranslationSemantic Similarity	—Unverified
Sematch: Semantic Entity Search from Knowledge Graph	Jun 1, 2015	Entity LinkingNatural Language Queries	CodeCode Available
An Open-source Framework for Multi-level Semantic Similarity Measurement	Jun 1, 2015	Information RetrievalMachine Translation	—Unverified
Paraphrase Identification and Semantic Similarity in Twitter with Simple Features	Jun 1, 2015	Information RetrievalMachine Translation	—Unverified
MathLingBudapest: Concept Networks for Semantic Similarity	Jun 1, 2015	Graph SimilaritySemantic Similarity	CodeCode Available
FBK-HLT: An Effective System for Paraphrase Identification and Semantic Similarity in Twitter	Jun 1, 2015	Information RetrievalMachine Translation	—Unverified
Ebiquity: Paraphrase and Semantic Similarity in Twitter using Skipgrams	Jun 1, 2015	Semantic SimilaritySemantic Textual Similarity	—Unverified
MITRE: Seven Systems for Semantic Similarity in Tweets	Jun 1, 2015	Information RetrievalMachine Translation	—Unverified
Reserating the awesometastic: An automatic extension of the WordNet taxonomy for novel terms	May 1, 2015	Information RetrievalLEMMA	—Unverified
Aligning Sentences from Standard Wikipedia to Simple Wikipedia	May 1, 2015	ArticlesLanguage Acquisition	—Unverified
So similar and yet incompatible: Toward the automated identification of semantically compatible words	May 1, 2015	Semantic SimilaritySemantic Textual Similarity	—Unverified
NASARI: a Novel Approach to a Semantically-Aware Representation of Items	May 1, 2015	ClusteringDimensionality Reduction	—Unverified
Random Walks and Neural Network Language Models on Knowledge Bases	May 1, 2015	Semantic SimilaritySemantic Textual Similarity	—Unverified
Texts in, meaning out: neural language models in semantic similarity task for Russian	Apr 30, 2015	Semantic SimilaritySemantic Textual Similarity	—Unverified
Joint Learning of Distributed Representations for Images and Texts	Apr 13, 2015	Semantic SimilaritySemantic Textual Similarity	—Unverified
BitSim: An Algebraic Similarity Measure for Description Logics Concepts	Mar 19, 2015	Semantic correspondenceSemantic Similarity	—Unverified
Short Text Hashing Improved by Integrating Multi-Granularity Topics and Tags	Mar 10, 2015	Semantic SimilaritySemantic Textual Similarity	CodeCode Available
Context-Dependent Translation Selection Using Convolutional Neural Network	Mar 9, 2015	Machine TranslationSemantic Similarity	—Unverified
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks	Feb 28, 2015	General ClassificationSemantic Similarity	CodeCode Available
Probabilistic Zero-shot Classification with Semantic Rankings	Feb 27, 2015	ClassificationGeneral Classification	—Unverified
Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval	Jan 26, 2015	Image RetrievalMulti-Label Image Retrieval	—Unverified
Higher-order Lexical Semantic Models for Non-factoid Answer Reranking	Jan 1, 2015	AllOpen-Domain Question Answering	—Unverified

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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