SOTAVerified

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 1401–1450 of 1564 papers

TitleStatusHype
Sinhala Short Sentence Similarity Calculation using Corpus-Based and Knowledge-Based Similarity Measures—0
'Part'ly first among equals: Semantic part-based benchmarking for state-of-the-art object recognition systems—0
Instance-aware Image and Sentence Matching with Selective Multimodal LSTM—0
SimDoc: Topic Sequence Alignment based Document Similarity Framework—0
Relating semantic similarity and semantic association to how humans label other people—0
Retrofitting Word Vectors of MeSH Terms to Improve Semantic Similarity Measures—0
Modelling Sentence Pairs with Tree-structured Attentive EncoderCode0
Are Word Embedding-based Features Useful for Sarcasm Detection?—0
Visual Fashion-Product Search at SK Planet—0
Semantic Similarity Strategies for Job Title Classification—0
Detecting Singleton Review Spammers Using Semantic Similarity—0
Automatic Visual Theme Discovery from Joint Image and Text Corpora—0
Improving Correlation with Human Judgments by Integrating Semantic Similarity with Second--Order Vectors—0
A Large-Scale Multilingual Disambiguation of Glosses—0
Using Semantic Similarity for Input Topic Identification in Crawling-based Web Application TestingCode0
Proceedings of the LexSem+Logics Workshop 2016—0
Bridging the Gap: Incorporating a Semantic Similarity Measure for Effectively Mapping PubMed Queries to Documents—0
De-Conflated Semantic RepresentationsCode0
Exponential Family Embeddings—0
Measuring Semantic Similarity of Words Using Concept NetworksCode0
Discourse Relation Sense Classification Using Cross-argument Semantic Similarity Based on Word Embeddings—0
SSDH: Semi-supervised Deep Hashing for Large Scale Image Retrieval—0
Machine Learned Resume-Job Matching Solution—0
Tweet2Vec: Learning Tweet Embeddings Using Character-level CNN-LSTM Encoder-Decoder—0
A Novel Information Theoretic Framework for Finding Semantic Similarity in WordNet—0
A Vector Space for Distributional Semantics for Entailment—0
Representation learning for very short texts using weighted word embedding aggregationCode0
Finding the Topic of a Set of Images—0
A Game-Theoretic Approach to Word Sense Disambiguation—0
The word entropy of natural languages—0
Universal Correspondence Network—0
JUNITMZ at SemEval-2016 Task 1: Identifying Semantic Similarity Using Levenshtein Ratio—0
RTM at SemEval-2016 Task 1: Predicting Semantic Similarity with Referential Translation Machines and Related Statistics—0
RTM at SemEval-2016 Task 1: Predicting Semantic Similarity with Referential Translation Machines and Related Statistics—0
Samsung Poland NLP Team at SemEval-2016 Task 1: Necessity for diversity; combining recursive autoencoders, WordNet and ensemble methods to measure semantic similarity.—0
IHS-RD-Belarus at SemEval-2016 Task 1: Multistage Approach for Measuring Semantic Similarity—0
NaCTeM at SemEval-2016 Task 1: Inferring sentence-level semantic similarity from an ensemble of complementary lexical and sentence-level features—0
Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement—0
FBK HLT-MT at SemEval-2016 Task 1: Cross-lingual Semantic Similarity Measurement Using Quality Estimation Features and Compositional Bilingual Word Embeddings—0
VRep at SemEval-2016 Task 1 and Task 2: A System for Interpretable Semantic Similarity—0
DTSim at SemEval-2016 Task 1: Semantic Similarity Model Including Multi-Level Alignment and Vector-Based Compositional Semantics—0
BattRAE: Bidimensional Attention-Based Recursive Autoencoders for Learning Bilingual Phrase EmbeddingsCode0
Problems With Evaluation of Word Embeddings Using Word Similarity Tasks—0
Extending Monolingual Semantic Textual Similarity Task to Multiple Cross-lingual Settings—0
From Interoperable Annotations towards Interoperable Resources: A Multilingual Approach to the Analysis of Discourse—0
SemAligner: A Method and Tool for Aligning Chunks with Semantic Relation Types and Semantic Similarity Scores—0
Typology of Adjectives Benchmark for Compositional Distributional Models—0
A sense-based lexicon of count and mass expressions: The Bochum English Countability Lexicon—0
What does this Emoji Mean? A Vector Space Skip-Gram Model for Twitter Emojis—0
Cognitively Motivated Distributional Representations of Meaning—0
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All datasetsAnnotated corpus for semantic similarity of clinical trial outcomes (expanded corpus)Annotated corpus for semantic similarity of clinical trial outcomes (original corpus)SICKBIOSSESCHIP-STSClinicalSTSMedSTS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F193.38—Unverified
2SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F191.51—Unverified
3SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F190.69—Unverified
4BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F189.16—Unverified
5BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, expanded corpus")F189.12—Unverified
#ModelMetricClaimedVerifiedStatus
1BioBERT (pre-trained on PubMed abstracts + PMC, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.75—Unverified
2SciBERT cased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
3SciBERT uncased (SciVocab, fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F189.3—Unverified
4BERT-Base uncased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F186.8—Unverified
5BERT-Base cased (fine-tuned on "Annotated corpus for semantic similarity of clinical trial outcomes, original corpus")F184.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Doc2VecCMSE0.31—Unverified
2LSTM (Tai et al., 2015)MSE0.28—Unverified
3Bidirectional LSTM (Tai et al., 2015)MSE0.27—Unverified
4combine-skip (Kiros et al., 2015)MSE0.27—Unverified
5Dependency Tree-LSTM (Tai et al., 2015)MSE0.25—Unverified
#ModelMetricClaimedVerifiedStatus
1BioLinkBERT (large)Pearson Correlation0.94—Unverified
2BioLinkBERT (base)Pearson Correlation0.93—Unverified
3NCBI_BERT(base) (P+M)Pearson Correlation0.92—Unverified
#ModelMetricClaimedVerifiedStatus
1MacBERT-largeMacro F185.6—Unverified
#ModelMetricClaimedVerifiedStatus
1CharacterBERT (base, medical, ensemble)Pearson Correlation85.62—Unverified
#ModelMetricClaimedVerifiedStatus
1NCBI_BERT(base) (P+M)Pearson Correlation0.85—Unverified