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 1251–1275 of 1564 papers

Title	Date	Tasks	Status
A Spatial Model for Extracting and Visualizing Latent Discourse Structure in Text	Jul 1, 2018	Information RetrievalReading Comprehension	—Unverified
Injecting Lexical Contrast into Word Vectors by Guiding Vector Space Specialisation	Jul 1, 2018	Dialogue State TrackingRepresentation Learning	—Unverified
Learning Thematic Similarity Metric from Article Sections Using Triplet Networks	Jul 1, 2018	ArticlesClustering	—Unverified
WordNet Embeddings	Jul 1, 2018	Representation LearningSemantic Similarity	CodeCode Available
Paragraph-based complex networks: application to document classification and authenticity verification	Jun 22, 2018	DiversityDocument Classification	—Unverified
The Corpus Replication Task	Jun 20, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified
Deploying Deep Ranking Models for Search Verticals	Jun 6, 2018	BIG-bench Machine LearningSemantic Similarity	—Unverified
Semi-Supervised Clustering with Neural Networks	Jun 5, 2018	ClusteringDeep Clustering	—Unverified
UniMelb at SemEval-2018 Task 12: Generative Implication using LSTMs, Siamese Networks and Semantic Representations with Synonym Fuzzing	Jun 1, 2018	General ClassificationMulti-Task Learning	—Unverified
GKR: the Graphical Knowledge Representation for semantic parsing	Jun 1, 2018	Natural Language InferenceSemantic Parsing	—Unverified
THU\_NGN at SemEval-2018 Task 10: Capturing Discriminative Attributes with MLP-CNN model	Jun 1, 2018	AttributeSemantic Similarity	—Unverified
Measuring Frame Instance Relatedness	Jun 1, 2018	ClusteringReading Comprehension	—Unverified
Similarity Measures for the Detection of Clinical Conditions with Verbal Fluency Tasks	Jun 1, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified
Specialising Word Vectors for Lexical Entailment	Jun 1, 2018	Dialogue State TrackingLexical Entailment	CodeCode Available
SemEval-2018 Task 10: Capturing Discriminative Attributes	Jun 1, 2018	AttributeSemantic Similarity	—Unverified
Analogies in Complex Verb Meaning Shifts: the Effect of Affect in Semantic Similarity Models	Jun 1, 2018	General ClassificationSemantic Similarity	—Unverified
Multi-Label Transfer Learning for Multi-Relational Semantic Similarity	May 31, 2018	Multi-Task Learningregression	—Unverified
Legal Document Retrieval using Document Vector Embeddings and Deep Learning	May 27, 2018	Deep LearningInformation Retrieval	—Unverified
Weight Initialization in Neural Language Models	May 12, 2018	Semantic SimilaritySemantic Textual Similarity	—Unverified
A Rank-Based Similarity Metric for Word Embeddings	May 4, 2018	ClusteringOutlier Detection	—Unverified
SemR-11: A Multi-Lingual Gold-Standard for Semantic Similarity and Relatedness for Eleven Languages	May 1, 2018	Information RetrievalMachine Translation	—Unverified
Semantic Structure-based Unsupervised Deep Hashing	May 1, 2018	Deep HashingSemantic Similarity	CodeCode Available
OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction	Apr 29, 2018	Semantic SimilaritySemantic Textual Similarity	CodeCode Available
An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages	Apr 27, 2018	Semantic SimilaritySemantic Textual Similarity	CodeCode Available
Learning Semantic Textual Similarity from Conversations	Apr 20, 2018	Community Question AnsweringNatural Language Inference	CodeCode Available

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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 uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")	F1	89.3	—	Unverified
3	SciBERT cased (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