Research Chat Testing Procedure

Semantic Similarity and Research Chat: Semantic similarity measures how closely related two texts are in meaning, using vector representations to capture contextual relationships between words. In Research Chat, we utilize large, trained models specifically designed for semantic similarity between sentences, which is ideal for assessing the accuracy of summaries. For instance, Research Chat achieved a semantic similarity score of 95.23% for summarizing whole research papers, reflecting high accuracy in maintaining the original content's meaning. This robust measure of relevance ensures that summaries are coherent and representative of the source material, regardless of text length or phrasing.

Time Decrease Calculation: To evaluate the efficiency of Research Chat's summarization, we compare the time needed to read the original text versus the time required to read the summary. With an estimated reading speed of 300 words per minute (WPM), we calculate the percentage decrease in reading time. For example, if a 10,000-word document typically takes about 33.3 minutes to read, and the summary reduces the text to 2,000 words, it would take approximately 6.7 minutes to read the summary. This results in an approximate 80% decrease in reading time. In practice, Research Chat has demonstrated a significant reduction in reading time, with a summary efficiency score of 95.10% for whole research papers, showing how effectively the summarization process streamlines information consumption.

The Linsear Write Score: The Linsear Write Score is a readability formula that assesses text complexity based on sentence length and the number of polysyllabic words. It provides a numerical score that indicates how easily a text can be understood, with lower scores suggesting simpler readability. This score is particularly useful for analyzing technical texts, such as research papers, where the complexity of words and sentence structures can be higher. Research Chat’s summaries of technical documents have shown an impressive decrease of complexity, reflecting its effectiveness in simplifying complex information. On average, Research Chat's summaries show a decrease of 11% from their source documents, effectively reducing the complexity of the text.