Products
Report | January 2024
Recent Insights in Responsible AI Development in Defense, 2022-2024
This literature survey identifies the most relevant new research in AI and robotic systems ethics from January 1, 2022 to January 31, 2024. Our selection methodology consisted of traditional research methods as well as newer human-AI teaming, resulting in a process that was designed to leverage the expert human judgment we have in our research team, which we enhanced with a collection of AI and computational tools used to assist our research.
Tool | March 2024
TF-IDF Analysis Tool
This program helps analyze a collection of PDF documents and identify those containing the most unique information. It uses a technique called Term Frequency-Inverse Document Frequency (TF-IDF) to achieve this.
What is TF-IDF?
Imagine each document as a conversation. TF-IDF considers words like "the" or "and" to be common and not very informative, just like everyday words in a conversation. On the other hand, words specific to your research topic would be like technical terms used in that conversation.
Term Frequency (TF): TF-IDF considers how often a word appears within a single document. The more a specific word shows up in a particular PDF compared to common words, the higher its TF score.
Inverse Document Frequency (IDF): IDF focuses on how rare a word is across all the documents in your collection. If a word appears only in a few PDFs, it gets a high IDF score. By combining these scores (TF x IDF), TF-IDF helps identify documents that use specific vocabulary not found elsewhere in your collection. These documents are likely to contain the most unique and relevant information for your research.
