SOTAVerified

Term Extraction

Term Extraction, or Automated Term Extraction (ATE), is about extraction domain-specific terms from natural language text. For example, the sentence “We meta-analyzed mortality using random-effect models” contains the domain-specific single-word terms "meta-analyzed", "mortality" and the multi-word term "random-effect models".

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 131–140 of 160 papers

TitleStatusHype
Improving Patent Translation using Bilingual Term Extraction and Re-tokenization for Chinese--Japanese—0
Local-Global Vectors to Improve Unigram Terminology Extraction—0
Recognition of non-domain phrases in automatically extracted lists of terms—0
Unsupervised Word and Dependency Path Embeddings for Aspect Term Extraction—0
The ACL RD-TEC 2.0: A Language Resource for Evaluating Term Extraction and Entity Recognition Methods—0
Aspect based Sentiment Analysis in Hindi: Resource Creation and Evaluation—0
JATE 2.0: Java Automatic Term Extraction with Apache SolrCode0
Rude waiter but mouthwatering pastries! An exploratory study into Dutch Aspect-Based Sentiment Analysis—0
Rule-based Automatic Multi-word Term Extraction and Lemmatization—0
Neural Attention Models for Sequence Classification: Analysis and Application to Key Term Extraction and Dialogue Act Detection—0
Show:102550
← PrevPage 14 of 16Next →
All datasetsAWARESemEval 2014 Task 4 Laptop

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BaselineF1-Score0.82—Unverified
#ModelMetricClaimedVerifiedStatus
1Seq2Seq4ATEF1-Score0.8—Unverified