tools for semantic trajectory data mining. a importância de considerar a semântica t1 t2 t3 t4 t1...
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A importância de considerar a semântica
T1
T2T3
T4 T1
T2T3
T4
H
H
H
Hotel
RR
R Restaurant
CC
C Cinema
Padrão SEMÂNTICO
(a) Hotel p/ Restaurante, passando por SC(b) Cinema, passando por SC
Padrão Geométrico
SC
Afternoon or Thursday or 6:00PM – 8:00PM or RUSH-HOUR
IbisHotel or Hotel or Accommodation
STOPS at Multiple-Granularities (Bogorny 2009)
Stop at Ibis Hotel from 6:04PM to 7:42PM, september 16, 2010
space
time
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- the building blocks for semantic pattern discovery
An item is generated either from a stop or a move
An item is a set of complex information (space + time), that can be defined in many formats/types and at different granularities
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Building an ITEM for Data Mining (Bogorny 2009)
Formats/types for an item:
NameOnly: is the name of the stop/move STOPS: name of the spatial feature instance
• IbisHotel MOVES: name of the two stops which define the move
• SydneyAirport – IbisHotel
NameStart: is the name of the stop/move + start time IbisHotel [morning] --stopLouvreMuseum [weekend] --stop IbisHotel-SydneyAirport [10:00AM-11:00AM] --move
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Building an ITEM for Data Mining (Bogorny 2009)
NameEnd: name of a stop/move + end time IbisHotel[morning] stop IbisHotel-SydneyAirport[10:00AM-11:00AM] move
NameStartEnd: name of a stop/move + start time + end time IbisHotel[08:00AM-11:00AM][1:00pm-6:00pm] stopLouvreMuseum[morning][afternoon] stopSydenyAirport– IbisHotel [10:00AM-11:00PM] [10:00AM-
6:00PM]
Multiple-Granularity Semantic Trajectory DMQL (Bogorny 2009)
ST-DMQL is an approach to semantically enrich trajectories with domain information
Autormatically tranforms these semantic information into different space and time granularities
Extracts frequent patterns, association rules and sequential patterns from semantic trajectories
Multiple Level Semantic Sequential Patterns
Large Sequences of Length 2 (ITEM=SPACE+Start_Time)
(41803_street_5, 41803_street_5) Support: 7
(41803_street_4, 41803_street_4) Support: 9
(41803_street_4, 66655_street_4) Support: 5
(41803_street_2, 41803_street_2) Support: 6
(41803_street_8, 41803_street_8) Support: 5
(41803_street_3, 0_unknown_3) Support: 5
gid
Spatial feature type (stop name)
time unit = month
Large Sequences of Length 2 (ITEM=SPACE+Start_Time)
(41803_street_tuesday,41803_street_tuesday) Support: 9
(41803_street_tuesday,66655_street_tuesday) Support: 5
(41803_street_monday,66655_street_monday) Support: 5
(41803_street_monday,41803_street_monday) Support: 11
(41803_street_monday,0_unknown_monday) Support: 5
(41803_street_thursday,41803_street_thursday) Support: 13
(41803_street_thursday,0_unknown_thursday) Support: 6
(41803_street_wednesday,41803_street_wednesday) Support: 7
gid
Spatial feature type (stop name)
Time unit = Day of the week
Multiple Level Semantic Sequential Patterns
13
item=name(instance) + start Time(month)
Large Sequences of Length 2
(41803_ruas_5,41803_ruas_5) Support: 7
(41803_ruas_4,41803_ruas_4) Support: 9
(41803_ruas_4,66655_ruas_4) Support: 5
(41803_ruas_2,41803_ruas_2) Support: 6
(41803_ruas_8,41803_ruas_8) Support: 5
(41803_ruas_3,0_unknown_3) Support: 5
gid
Spatial feature type
month
14
item=name(instance) + startTime(weekday/weekend)
Large Sequences of Length 3 (41803_ruas_weekday,41803_ruas_weekday,66655_ruas_weekday) Support: 6 (41803_ruas_weekday,66640_ruas_weekday,66655_ruas_weekday) Support: 7
Large Sequences of Length 2 (0_unknown_weekday,41803_ruas_weekday) Support: 5 (41803_ruas_weekday,0_unknown_weekday) Support: 16 (41803_ruas_weekday,66658_ruas_weekday) Support: 8
Large Sequences of Length 1 (66584_ruas_weekday) Support: 10
15
item=name(instance) + start time = day of the week
Large Sequences of Length 2
(41803_ruas_tuesday,41803_ruas_tuesday) Support: 9
(41803_ruas_tuesday,66655_ruas_tuesday) Support: 5
(41803_ruas_monday,66655_ruas_monday) Support: 5
(41803_ruas_monday,41803_ruas_monday) Support: 11
(41803_ruas_monday,0_unknown_monday) Support: 5
(41803_ruas_thursday,41803_ruas_thursday) Support: 13
(41803_ruas_thursday,0_unknown_thursday) Support: 6
(41803_ruas_wednesday,41803_ruas_wednesday) Support: 7
22
Weka-STDPM
• Ferramenta criada por alunos da UFRGS e UFSC• Extensao da Ferramenta Weka, criada na Nova Zelandia para Mineracao de dados