This paper presents an integrated framework for SpatioTemporal-Textual
(STT) information retrieval and knowledge
discovery system. The proposed ensemble framework contains
an efficient STT search engine with multiple indexing, ranking
and scoring schemes, an effective STT pattern miner with
Spatio-Temporal (ST) analytics, and novel STT topic modeling.
Specifically, we design an effective prediction prototype with a
third-order linear regression model, and present an innovative
STT topic modeling relevance ranker to score documents based
on inherent STT features under topical space. We demonstrate
the framework with a crime dataset from the Washington, DC
area from