arXiv:2606.30824v1 Announce Type: cross Abstract: We introduce Information Terra, a narrative-anchored semantic-first projection that places a document corpus on an Earth-like globe whose poles are two user-chosen endpoint documents and whose prime meridian is the great-circle geodesic between them on the embedding hypersphere -- so latitude encodes narrative progress and longitude thematic deviation. Land features are recovered from document density via kernel density estimation and labeled by theme. A narrative trail built from the underlying narrative coherence graph, and constrained to be
The proliferation of digital documents and the advancement of embedding techniques necessitate more intuitive and powerful ways to navigate and comprehend large information spaces.
This development offers a novel and potentially highly effective method for sense-making in vast document corpuses, improving information retrieval and thematic understanding for strategic decision-makers.
The ability to visually and narratively anchor document embeddings on an Earth-like globe redefines how users interact with and extract insights from complex data sets, moving beyond traditional search and clustering.
- · Analysts and researchers
- · Intelligence agencies
- · Large language model developers
- · Document management systems
- · Basic keyword search tools
- · Disorganized data archives
Improved efficiency in qualitative data analysis and synthesis across various domains.
Reduced cognitive load for navigating complex information, accelerating research and development cycles.
Potential for new forms of narrative-driven AI agent architectures that leverage this semantic-first projection for decision-making.
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Read at arXiv cs.CL