DeepRead uses AI to transform books into interconnected knowledge networks, present content structures in the form of visual maps, and support multi-dimensional exploration and in-depth mining.
liujuntao123/DeepRead It is a tool that uses AI technology to transform book content into a “knowledge map”.
project overview
according to the project README，DeepRead The vision is to “break the limitations of linear reading and build a three-dimensional knowledge system.” It uses AI tools to construct the content in books into an interactive knowledge network graph (Knowledge Map), thereby improving reading understanding, memory and correlation capabilities
Core functional characteristics
- Intelligent parsing engine
- Parse entire book content using the Big Language Model (LLM)
- Automatically extract key elements such as people, events, concepts, places, etc.
- Mining the complex relationships between these elements
- Knowledge map generation
- Build a multi-level and multi-dimensional three-dimensional structural map
- Supports two-way links to facilitate rapid jumps between knowledge nodes
- Automatic classification and labeling management of graph content based on topics
- example shows
Several example maps are also provided in the README:
– The role relationship map of “The Romance of the Three Kingdoms”(94 nodes)
– The roadmap for learning from “Journey to the West”(192 nodes)
– Books such as “Dream of the Red Chamber”,”Water Margin”,”Hundred Years of Solitude”,”Das Kapital” and “The Metaphors We Live by” also have corresponding visual maps displayed
to sum up
DeepRead is a project that parses book texts through AI and automatically generates book knowledge maps. It transforms reading from an originally linear and artificially organized information processing method to a visual and freely jump-able knowledge network, thereby improving reading efficiency and depth.
Online experience:https://deepread.aizhi.site/
Github：https://github.com/liujuntao123/DeepRead
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