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User online behavior and interests will play a central role in future mobile networks. We introduce a systematic method for large-scale multi-dimensional modeling and analysis of online activity and mobility for thousands of mobile users across 79 buildings over a variety of web domains. We propose a modeling approach based on kind of neural-networks, called self-organizing maps (SOM), for discovering, organizing and visualizing different mobile users' trends from billions of WLAN records. We find surprisingly that users' trends based on domains and locations can be accurately modeled using a self-organizing map with clearly distinct characteristics. We also find many non-trivial correlations between different types of web domains and locations.
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Stored only when both papers are in the corpus — 9 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.