Dataset details.

<p>Dataset details.</p

Topic model of geo life-style pattern inference.

<p>White circles represent random variables, shaded circles represent observed variables, rectangles represent the repetitiveness of the data, and arrows represent the dependency among the entities.</p

Results of user interests pattern model.

<p>Results of user interests pattern model.</p

Perplexity versus the number of life-style patterns.

<p>Perplexity versus the number of life-style patterns.</p

Check-in distribution.

<p>Check-in distribution.</p

Results of user geo context pattern model.

<p>Results of user geo context pattern model.</p

Components of the proposed approach to enrich the location contexts of user check-ins and use it for modeling geo life-style patterns.

<p>Components of the proposed approach to enrich the location contexts of user check-ins and use it for modeling geo life-style patterns.</p

Examples of location categories used and the list of the categories for which names are used.

<p>Examples of location categories used and the list of the categories for which names are used.</p

The distribution of location contexts of a user, the pattern proportion and the activity location distributions for the corresponding patterns.

<p>(A)User 1 having few dominating activity location choice patterns. For the pattern proportion of the user, only the patterns with probabilities not less than 0.05 are shown. For the activity location distribution, only the locations with frequencies not less than five are presented; the data contains 617 check-ins of the user. (B) User 2 having a diverse activity location choice patterns. For the pattern proportion of the user, only the patterns with probabilities not less than 0.05 are shown. For the activity location distribution, only the locations with frequencies not less than two are presented; the data contains 145 check-ins of the user.</p

Median household weekly rent against the corresponding normalized accessibility values of the UCLs.

<p>Median household weekly rent against the corresponding normalized accessibility values of the UCLs.</p