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Showing 1 to 4 of 4 for “"Semantic Textual Similarity"”.

  1. Deep learning based semantic textual similarity for applications in translation technology

    Semantic Textual Similarity (STS) measures the equivalence of meanings between two textual segments. It is a fundamental task for many natural language processing applications. In this study, we focus on employing STS in the context of translation technology. We start by developing models to …

    wlv Repository record for Deep learning based semantic textual similarity for applications in translation technology (opens in a new tab)

  2. A Framework for Semantic Textual Similarity Integration with Requirements and System Models

    … descriptions, and synonyms. The algorithm uses semantic textual similarity to identify similarities between requirements and these component attributes to estimate which components of a system are affected by which requirement(s). The algorithm attempts to identify direct relationships between …

    mit Repository record for A Framework for Semantic Textual Similarity Integration with Requirements and System Models (opens in a new tab)

  3. Geometries of word embeddings

    … of its context, while GPT and BERT are contextualized whose representations will change corresponding to the semantics conveyed by its surrounding words. In this dissertation, we study four problems associated with the geometrics of word embeddings. First, we demonstrate a very simple, and …

    uiuc Repository record for Geometries of word embeddings (opens in a new tab)

  4. Methods for Measuring Semantic Similarity of Texts

    Measuring semantic similarity is a task needed in many Natural Language Processing (NLP) applications. For example, in Machine Translation evaluation, semantic similarity is used to assess the quality of the machine translation output by measuring the degree of equivalence between a reference …

    wlv Repository record for Methods for Measuring Semantic Similarity of Texts (opens in a new tab)