A method for semantic textual similarity on long texts [PDF]
PeerJ Computer ScienceThis work introduces a method for the semantic similarity of long documents using sentence transformers and large language models. The method detects relevant information from a pair of long texts by exploiting sentence transformers and large language ...
Omar Zatarain +2 more
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UESTS: An Unsupervised Ensemble Semantic Textual Similarity Method [PDF]
IEEE Access, 2019 Semantic textual similarity (STS) is the task of assessing the degree of similarity between two texts in terms of meaning. Several approaches have been proposed in the literature to determine the semantic similarity between texts. The most promising work
Basma Hassan +3 more
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ALBERT-Based Self-Ensemble Model With Semisupervised Learning and Data Augmentation for Clinical Semantic Textual Similarity Calculation: Algorithm Validation Study [PDF]
JMIR Medical Informatics, 2021 BackgroundIn recent years, with increases in the amount of information available and the importance of information screening, increased attention has been paid to the calculation of textual semantic similarity.
Li, Junyi, Zhang, Xuejie, Zhou, Xiaobing
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The 2019 n2c2/OHNLP Track on Clinical Semantic Textual Similarity: Overview [PDF]
JMIR Medical Informatics, 2020 BackgroundSemantic textual similarity is a common task in the general English domain to assess the degree to which the underlying semantics of 2 text segments are equivalent to each other.
Wang, Yanshan +5 more
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Semantic textual similarity for modern standard and dialectal Arabic using transfer learning. [PDF]
PLoS ONE, 2022 Semantic Textual Similarity (STS) is the task of identifying the semantic correlation between two sentences of the same or different languages. STS is an important task in natural language processing because it has many applications in different domains ...
Mansour Al Sulaiman +5 more
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Measurement of Semantic Textual Similarity in Clinical Texts: Comparison of Transformer-Based Models [PDF]
JMIR Medical Informatics, 2020 BackgroundSemantic textual similarity (STS) is one of the fundamental tasks in natural language processing (NLP). Many shared tasks and corpora for STS have been organized and curated in the general English domain; however, such resources are limited in ...
Yang, Xi +5 more
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Linking Datasets Using Semantic Textual Similarity [PDF]
Cybernetics and Information Technologies, 2018 Linked data has been widely recognized as an important paradigm for representing data and one of the most important aspects of supporting its use is discovery of links between datasets.
McCrae John P., Buitelaar Paul
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Benchmarking Natural Language Inference and Semantic Textual Similarity for Portuguese
Information, 2020 Two sentences can be related in many different ways. Distinct tasks in natural language processing aim to identify different semantic relations between sentences.
Pedro Fialho +2 more
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Linking Symptom Inventories Using Semantic Textual Similarity [PDF]
Journal of NeurotraumaAn extensive library of symptom inventories has been developed over time to measure clinical symptoms of traumatic brain injury (TBI), but this variety has led to several long-standing issues. Most notably, results drawn from different settings and studies are not comparable. This creates a fundamental problem in TBI diagnostics and outcome prediction,
William Walker +2 more
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Applied Sciences, 2022 Semantic Textual Similarity (STS) is an important task in the area of Natural Language Processing (NLP) that measures the similarity of the underlying semantics of two texts.
Somaiyeh Dehghan, Mehmet Fatih Amasyali
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