Legal Document Summarizer — TextRank Live (2D): Visualizing Sentence Similarity in Legal Texts

What Is TextRank?

TextRank is a natural language processing algorithm that uses the PageRank technique from search engines to rank sentences in a text based on their semantic similarity. It models the text as a graph where nodes represent sentences and edges represent similarities between them.

The algorithm iteratively updates the importance score of each sentence, converging to a stable ranking that highlights the most representative sentences for summarization.

How TextRank Works

TextRank starts by constructing a graph where each node corresponds to a sentence in the document. Edges between nodes are weighted based on the similarity of their content, often calculated using techniques like TF-IDF or cosine similarity.

The algorithm then applies iterative updates to these weights, similar to how PageRank updates link weights. This process continues until the importance scores stabilize, resulting in a ranked list of sentences that form an effective summary.

Why It Matters for Legal Documents

Legal documents are often lengthy and complex, making them challenging to read and understand at a glance. TextRank can help identify key points quickly by summarizing the document into its most important sentences.

This is particularly useful in legal contexts where time efficiency and precision are crucial.

Real-World Applications

TextRank has been applied to various fields, including legal documents, to automate the process of creating concise summaries that capture the essence of lengthy texts.

For example, it can be used by lawyers to quickly grasp the main points of a contract or by judges to summarize case law for faster decision-making.

Frequently asked questions

Try it live

Everything above runs in your browser — open Legal Document Summarizer — TextRank Live (2D) and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.