Estimating the semantic similarity between text data is one of the challenging and open research problems in the field of Natural Language Processing(NLP).The versatility(多样性) of natural language makes it difficult to define rule-based methods for determining semantic similarity measures(NLP的多样性...
1. Semantic Textual Similarity(STS):判断两个句子的语义相似程度; 2.Natural Language Inference (NLI):也叫Recognizing Textual Entailment (RTE),判断两个句子在语义上是否存在推断关系,相对任务1更复杂一些,不仅仅是考虑相似,而且也考虑了推理; 3.Paraphrase Identification (PI):判断两个句子是否表达同样的意思; ...
Semantic similarity measures are widely used in Natural Language Processing (NLP) and Information Retrieval (IR). The work proposed here uses web based metrics to compute the semantic similarity between words or terms and also compares with the state-of-the-art. For a computer to decide the ...
句子对建模是NLP,NLU中比较基础,并扮演着重要角色的任务,主要集中在语义理解,语义交互上,也是我自己的一个研究方向,大致有这几类任务 Semantic Textual Similarity (STS) :判断两个句子的语义相似程度(measureing the degree of equivalence in the underlying semantics of paired snippets of text) Natural Language ...
nlpswiftinformation-retrievalquestion-answeringsemantic-similaritypretrained-modelssemantic-searchcoremltext-embeddingsvector-embeddingsapple-neural-engine UpdatedJun 4, 2024 Swift all kinds of baseline models for sentence similarity 句子对语义相似度模型
https://paperswithcode.com/sota/semantic-textual-similarity-on-senteval paperwithcode是一个很好的网站 然后github上关于Semantic Textual Similarity的信息综合帖,Awesome-Repositories-for-NLI-and-Semantic-Similarity.md https://gist.github.com/GhibliField/c3c97b742d346baa5f14b3a796c12a4a ...
Semantic Textual Similarity (STS) is a foundational NLP task and can be used in a wide range of tasks. To determine the STS of two texts, hundreds of different STS systems exist, however, for an NLP system designer, it is hard to decide which system is the best one. To answer this ...
2016. MayoNLP at SemEval-2016 Task 1: Seman- tic Textual Similarity based on Lexical Semantic Net and Deep Learning Semantic Model. In Proceed- ings of the 10th International Workshop on Semantic Evaluation (SemEval-2016). San ... N Afzal,Y Wang,H Liu - International Workshop on Semantic...
语义熵的主要灵感是通过将不确定性估计问题转化到语义空间来正面解决自然语言的语义不变性。 语义熵在某种程度上解决了token重要性不同的问题。 实验分析 metric:AUROC Model:OPT Datasets:CoQA、TriviaQA Baselines:Predictive entropy、Length-normalised predictive entropy、p(True)、Lexical similarity...
而最近,Google向我们展示了NLP方面最新的研究成果,针对句子的语义表征(semantic representation)及其生成方法。方法一,Learning Semantic Textual Similarity from Conversations。原理相当简单——在会话场景下,如果某些句子的回复总是对应一个相同的句子,那么这些句子在语义上就认为是相似。例如: How old are you?和What ...