Streamlining Scientific Literature Discovery with Semantic Similarity Analysis

The aim of this project was to expedite the process of discovering scientific literature on a particular topic, as it is often laborious to sift through and evaluate abstracts to find pertinent ones for research purposes.

Dr. Donnacha Daly

COO

New mobile apps to keep an eye on

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What new social media mobile apps are available in 2022?

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Use new social media apps as marketing funnels

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Try out Twitter Spaces or Clubhouse on iPhone

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What app are you currently experimenting on?

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Streamlining Scientific Literature Discovery with Semantic Similarity Analysis

The goal of this project was to streamline the process of discovering scientific literature related to a particular topic, as the task of sifting through and evaluating abstracts can be time-consuming and laborious for researchers. To expedite this process, the project utilized the arXiv API to retrieve results matching specific keywords. The retrieved results were then compared using semantic similarity analysis to identify relevant literature quickly and efficiently. This method saves researchers a significant amount of time by eliminating the need to read through numerous abstracts to identify the most pertinent ones for their research. The project's outcome offers a valuable tool for researchers to compare existing literature in a specific field and identify gaps that need further investigation.