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semantic-text-similarity's Introduction

Semantic-Text-Similarity

Task- Finding Semantic Textual Similarity

PROBLEM STATEMENT

  • Given two paragraphs, quantify the degree of similarity between the two text-based on Semantic similarity. Semantic Textual Similarity (STS) assesses the degree to which two sentences are semantically equivalent to each other. The STS task is motivated by the observation that accurately modelling the meaning similarity of sentences is a foundational language understanding problem relevant to numerous applications including machine translation (MT), summarization, generation, question-answering (QA), short answer grading, semantic search.
  • STS is the assessment of pairs of sentences according to their degree of semantic similarity. The task involves producing real-valued similarity scores for sentence pairs.

Dataset Link:

https://drive.google.com/file/d/1OSJR7wLfNunt1WPD03Kj63WAH6Ch1cFf/view?ts=5db2bda5

  • The data contains a pair of paragraphs. These text paragraphs are randomly sampled from a raw dataset. Each pair of the sentence may or may not be semantically similar. The candidate is to predict a value between 0-1 indicating a degree of similarity between the pair of text paras. 0 means highly similar 1 means highly dissimilar

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Contributors

eshan-agarwal avatar

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