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GD-ML
/

CCN

Tasks:

Tabular Classification

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complete_rate string	label string	navi_scene string	route_features string	kdifflen string	kdiffeta string	kdiffhighwaylen string	kdifftolllenholi string	kdifflight string	kdiff14 string	kdiff15 string	kdiffslowlen string	kdiffcongeslen string	kdiffstationallen string	kdiffunknownlen string	kdiffturnleft string	kdiffturnright string	kdiffturnleftf string	kdiffturnrightf string	kdiffturnleftb string	kdiffturnrightb string	kdiffturnuturn string	kdiffvalidturnnum2 string	kdiffodfamrate string	kdiffavgodfamfreq string	kdiffstartdistance string	kdiffnonmotorlen string	ksimilarity string	kbclocalwinding string	kbcstarthardaction string	kbcparallelroad string	kbccongestionhigh string	kbcdifflenexcessive string	kbcgoaround string	kbcthreebad string	kbcfourbad string	kbconeextremebad string	kbctwoextremebad string	kbcthreeextremebad string	kbcfourextremebad string	diff_coverage string	route_trace_overlap string	kdiffweightedfamiliarfreq string	kdiffweightedfamiliarprob string	kdiffavgfamfreq string	kdifffamrate string	kdifflineardis string	click_path_pos string	value_kpathhistorystatus string	value_kpathstatus string	value_kpathlengthratio string	value_kpathodist string	value_kpathddist string	value_kpathoposition string	value_kpathdposition string	value_kpathdeltaday string	indice_fam_freq string	indice_fam_freq_num string	links_sphdistance string	links_length string	links_dir string	links_dir_to_d string	links_dir_to_od string	links_dir_enter string	links_dir_leave string	links_dir_delta string	links_eta string	weighted_heat_freq_feat string	weighted_heat_prob_feat string	long_features string	group_id int64
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Towards Full Candidate Interaction: A Comprehensive Comparison Network for Better Route Recommendation

This is the dataset for our paper.
The following table contains the feature dimensions and key features of our dataset.

Feature Type	Interpretation	Shape	Some Key Features
Route Features	Used to describe each route, including static features, dynamic features, and trajectory statistical features	N * 62	The estimated time of arrival for the route The total distance length of the route
Scene Features	Represent the contextual information of route recommendation	1 * 10	Request time User familiarity with the origin and destination
Comparison-Level Features	Represents the attributes of the non-overlapping segments between two routes	N * N * 27	Comparison diff eta Comparison diff distance

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