@@ -231,10 +231,13 @@ You can see examples of how to use PyMove [here](https://github.com/InsightLab/P
231231- 1: ** Spatial Trajectories** &rarr ; ` pymove.core `
232232 - ` MoveDataFrame `
233233 - ` DiscreteMoveDataFrame `
234+
234235- 2: ** Stay Point Detection** &rarr ; ` pymove.preprocessing.stay_point_detection `
235236 - ` create_or_update_move_stop_by_dist_time `
236237 - ` create_or_update_move_and_stop_by_radius `
238+
237239- 3: ** Map-Matching** &rarr ; ` pymove-osmnx `
240+
238241- 4: ** Noise Filtering** &rarr ; ` pymove.preprocessing.filters `
239242 - ` by_bbox `
240243 - ` by_datetime `
@@ -249,29 +252,42 @@ You can see examples of how to use PyMove [here](https://github.com/InsightLab/P
249252 - ` clean_trajectories_with_few_points `
250253 - ` clean_trajectories_short_and_few_points `
251254 - ` clean_id_by_time_max `
255+
252256- 5: ** Compression** &rarr ; ` pymove.preprocessing.compression `
253257 - ` compress_segment_stop_to_point `
258+
254259- 6: ** Segmentation** &rarr ; ` pymove.preprocessing.segmentation `
255260 - ` bbox_split `
256261 - ` by_dist_time_speed `
257262 - ` by_max_dist `
258263 - ` by_max_time `
259264 - ` by_max_speed `
265+
260266- 7: ** Distance of Trajectory** &rarr ; ` pymove.query.query `
261267 - ` range_query `
262268 - ` knn_query `
269+
263270- 8: ** Query Historical Trajectories**
271+
264272- 9: ** Managing Recent Trajectories**
273+
265274- 10: ** Privacy Preserving**
275+
266276- 11: ** Reducing Uncertainty**
277+
267278- 12: ** Moving Together Patterns**
279+
268280- 13: ** Clustering** &rarr ; ` pymove.models.pattern_mining.clustering `
269281 - ` elbow_method `
270282 - ` gap_statistics `
271283 - ` dbscan_clustering `
284+
272285- 14: ** Freq. Seq. Patterns**
286+
273287- 15: ** Periodic Patterns**
288+
274289- 16: ** Trajectory Classification**
290+
275291- 17: ** Trajectory Outlier / Anomaly Detection** &rarr ; ` pymove.semantic.semantic `
276292 - ` outliers `
277293 - ` create_or_update_out_of_the_bbox `
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