Top

Published in:

2021 | OriginalPaper | Chapter

9. Multi-attribute Trajectory Data Management

Author : Jianqiu Xu

Published in: Handbook of Big Geospatial Data

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Motivated by the trend of enriching the knowledge about movement data, this chapter introduces representing and querying multi-attribute trajectories in a database system. Such a trajectory contains a sequence of time-stamped locations and a set of descriptive attributes. Multi-attribute trajectories mainly deal with attributes describing characteristics of objects, i.e., attributes that are not relevant to locations. This differs from semantic and activity trajectories in the literature that focus on location-dependent information. A range of novel queries are incurred that integrate both spatio-temporal data and attributes into the evaluation. To enhance the query performance, a hybrid and flexible index is developed to manage multi-attribute trajectories. Efficiently updating the structure is also presented. Query algorithms are proposed, accompanied with optimization strategies. Furthermore, the chapter introduces the system development, reports the performance evaluation and points out future directions.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

previous chapter Semantic Trajectories Data Models

next chapter Mining Colocation from Big Geo-Spatial Event Data on GPU

Given three rectangles a, b, c, each contains a set of points inside. We aim to find the nearest point to a given point inside a. Let Max(b, a) and Min(c, a) denote the maximum and minimum distances between two rectangles. If Max(b, a) ≤ Min(c, a), then no point inside the rectangle c can be closer than a point in the rectangle b to a. As a consequence, we can omit c when searching for the nearest neighbor to a.

The space is contained by the node but there are few or no data objects. One can also call this dead space (Tao and Papadias 2001), meaning that the area will be evaluated but few objects are there or even no object exists.

Alvares LO, Bogorny V, Kuijpers B, Moelans B, Fern JA, Macedo ED, Palma AT (2007) Towards semantic trajectory knowledge discovery. Data Mining and Knowl Discov

Bentley JL, Ottmann T (1979) Algorithms for reporting and counting geometric intersections. IEEE Trans Comput 28(9):643–647MATHCrossRef

Bercken J, Seeger B (2001) An evaluation of generic bulk loading techniques. In: VLDB, pp 461–470

Bercken J, Seeger B, Widmayer P (1997) A generic approach to bulk loading multidimensional index structures. In: VLDB, pp 406–415

Chakka VP, Everspaugh A, Patel JM (2003) Indexing large trajectory data sets with seti. In: CIDR

Chen Z, Tao Shen H, Zhou X, Zheng Y, Xie X (2010) Searching trajectories by locations: an efficiency study. In: SIGMOD, pp 255–266

Chen L, Cong G, Jensen CS, Wu D (2013) Spatial keyword query processing: an experimental evaluation. PVLDB 6(3):217–228

Cong G, Jensen CS, Wu D (2009) Efficient retrieval of the top-k most relevant spatial web objects. PVLDB 2(1):337–348

de Almeida VT, Güting RH (2005) Indexing the trajectories of moving objects in networks. GeoInformatica 9(1):33–60CrossRef

De Felipe I, Hristidis V, Rishe N (2008) Keyword search on spatial databases. In: ICDE, pp 656–665

Dinh L, Aref WG, Mokbel MF (2010) Spatio-temporal access methods: part 2 (2003–2010). IEEE Data Eng Bull 33(2):46–55

Forlizzi L, Güting RH, Nardelli E, Schneider M (2000) A data model and data structures for moving objects databases. In: SIGMOD, pp 319–330

Frentzos E (2003) Indexing objects moving on fixed networks. In: SSTD, pp 289–305

Frentzos E, Gratsias K, Pelekis N, Theodoridis Y (2005) Nearest neighbor search on moving object trajectories. In: SSTD, pp 328–345

Frentzos E, Gratsias K, Pelekis N, Theodoridis Y (2007) Algorithms for nearest neighbor search on moving object trajectories. GeoInformatica 11(2):159–193CrossRef

Güting RH, Schneider M (2005) Moving objects databases. Morgan Kaufmann, AmsterdamMATH

Güting RH, Böhlen MH, Erwig M, Jensen CS, Lorentzos NA, Schneider M, Vazirgiannis M (2000) A foundation for representing and querying moving objects. ACM TODS 25(1):1–42CrossRef

Güting RH, Behr T, Düntgen C (2010a) SECONDO: a platform for moving objects database research and for publishing and integrating research implementations. IEEE Data Eng Bull 33(2):56–63

Güting RH, Behr T, Xu J (2010b) Efficient k-nearest neighbor search on moving object trajectories. VLDB J 19(5):687–714CrossRef

Güting RH, Valdés F, Damiani ML (2015) Symbolic trajectories. ACM Trans Spat Algorithms Syst 1(2):Article 7

Hadjieleftheriou M, Kollios G, Tsotras VJ, Gunopulos D (2002) Efficient indexing of spatiotemporal objects. In: EDBT, pp 251–268

Han Y, Wang L, Zhang Y, Zhang W, Lin X (2015) Spatial keyword range search on trajectories. In: DASFAA, pp 223–240

Jensen CS, Lu H, Yang B (2009) Indexing the trajectories of moving objects in symbolic indoor space. In: SSTD, pp 208–227

Jeung H, Yiu ML, Zhou X, Jensen CS, Shen HT (2008) Discovery of convoys in trajectory databases. PVLDB 1(1):1068–1080

Lange R, Dürr F, Rothermel K (2011) Efficient real-time trajectory tracking. VLDB J 20(5):671–694CrossRef

Lee T, Park J, Lee S, et al (2015) Processing and optimizing main memory spatial-keyword queries. PVLDB 9(3):132–143

Long C, Wong RCW, Jagadish HV (2013) Direction-preserving trajectory simplification. PVLDB 6(10):949–960

Lu H, Cao X, Jensen CS (2012) A foundation for efficient indoor distance-aware query processing. In: ICDE, pp 438–449

Mauroux PC, Wu E, Madden S (2010) Trajstore: an adaptive storage system for very large trajectory data sets. In: ICDE, pp 109–120

Parent C, Spaccapietra S, Renso C, Andrienko GL, Andrienko NV, Bogorny V, Damiani ML, Gkoulalas-Divanis A, de Macêdo JAF, Pelekis N, Theodoridis Y, Yan Z (2013) Semantic trajectories modeling and analysis. ACM Comput Surv 45(4):42CrossRef

Pelanis M, Saltenis S, Jensen CS (2006) Indexing the past, present, and anticipated future positions of moving objects. ACM TODS 31(1):255–298CrossRef

Pfoser D, Jensen CS (2003) Indexing of network constrained moving objects. In: GIS, pp 25–32

Pfoser D, Jensen CS (2000) Novel approaches in query processing for moving object trajectories. In: VLDB, pp 395–406

Piorkowski M, Sarafijanovic-Djukic N, Grossglauser M CRAWDAD dataset epfl/mobility (v. 24 Feb 2009). http://crawdad.org/epfl/mobility/20090224

Popa IS, Zeitouni K, Oria V, Barth D, Vial S Indexing in-network trajectory flows. VLDB J 20(5):643–669 (2011)CrossRef

Rasetic S, Sander J, Elding J, Nascimento MA (2005) A trajectory splitting model for efficient spatio-temporal indexing. In: VLDB, pp 934–945

Song Z, Roussopoulos N (2003) Seb-tree: an approach to index continuously moving objects. In: MDM, pp 340–344

Su Y, Wu Y, Chen ALP (2007) Monitoring heterogeneous nearest neighbors for moving objects considering location-independent attributes. In: DASFAA, pp 300–312

Su H, Zheng K, Zeng K, Huang J, Sadiq SW, Yuan NJ, Zhou X (2015) Making sense of trajectory data: a partition-and-summarization approach. In: ICDE, pp 963–974

Tao Y, Papadias D (2001) Mv3r-tree: a spatio-temporal access method for timestamp and interval queries. In: VLDB, pp 431–440

Tong Y, Chen Y, Zhou Z, Chen L, Wang J, Yang Q, Ye J, Lv W (2017) The simpler the better: a unified approach to predicting original taxi demands based on large-scale online platforms. In: ACM SIGKDD, pp 1653–1662

Tong Y, Zeng Y, Zhou Z, Chen L, Ye J, Xu K (2018) A unified approach to route planning for shared mobility. PVLDB 11(11):1633–1646

Tzoumas K, Yiu ML, Jensen CS (2009) Workload-aware indexing of continuously moving objects. PVLDB 2(1):1186–1197

Valdés F, Güting RH (2014) Index-supported pattern matching on symbolic trajectories. In: ACM SIGSPATIAL, pp 53–62

Valdés F, Güting RH (2017) Index-supported pattern matching on tuples of time-dependent values. GeoInformatica 21(3):429–458CrossRef

Valdés F, Güting RH (2019) A framework for efficient multi-attribute movement data analysis. VLDB J 28(4):427–449CrossRef

Wang H, Zimmermann R (2011) Processing of continuous location-based range queries on moving objects in road networks. IEEE Trans Knowl Data Eng 23(7):1065–1078CrossRef

Wang W, Xu J (2017) A tool for 3d visualizing moving objects. In: APWeb-WAIM, pp 353–357

Wang X, Zhang Y, Zhang W, Lin X, Huang Z (2016) SKYPE: top-k spatial-keyword publish/subscribe over sliding window. PVLDB 9(7):588–599

Wei X, Xu J (2018) MDBF: a tool for monitoring database files. In: ER Workshops, pp 54–58

Wu D, Yiu ML, Cong G, Jensen CS (2012) Joint top-k spatial keyword query processing. IEEE Trans Knowl Data Eng 24(10):1889–1903CrossRef

Xu J, Güting RH (2012) Mwgen: a mini world generator. In: IEEE MDM, pp 258–267

Xu J, Güting RH (2013) A generic data model for moving objects. GeoInformatica 17(1):125–172CrossRef

Xu J, Güting RH (2017) Query and animate multi-attribute trajectory data. In: ACM CIKM, pp 2551–2554

Xu J, Güting RH, Qin X (2015a) Gmobench: benchmarking generic moving objects. GeoInformatica 19(2):227–276CrossRef

Xu J, Güting RH, Zheng Y (2015b) The TM-RTree: an index on generic moving objects for range queries. GeoInformatica 19(3):487–524CrossRef

Xu J, Güting RH, Gao Y (2018a) Continuous k nearest neighbor queries over large multi-attribute trajectories: a systematic approach. GeoInformatica 22(4):723–766CrossRef

Xu J, Lu H, Güting RH (2018b) Range queries on multi-attribute trajectories. IEEE Trans Knowl Data Eng 30(6):1206–1211CrossRef

Yan Z, Chakraborty D, Parent C, Spaccapietra S, Aberer K (2011) Semitri: a framework for semantic annotation of heterogeneous trajectories. In: EDBT, pp 259–270

Yao B, Xiao X, Li F, Wu Y (2014) Dynamic monitoring of optimal locations in road network databases. VLDB J 23(5):697–720CrossRef

Zhang C, Han J, Shou L, Lu J, La Porta TF (2014) Splitter: mining fine-grained sequential patterns in semantic trajectories. PVLDB 7(9):769–780

Zheng K, Su H (2015) Go beyond raw trajectory data: quality and semantics. IEEE Data Eng Bull 38(2):27–34

Zheng Y, Zhou X (2011) Computing with spatial trajectories. Springer, New YorkCrossRef

Zheng K, Shang S, Yuan NJ, Yang Y (2013a) Towards efficient search for activity trajectories. In: ICDE, pp 230–241

Zheng K, Zheng Y, Yuan NJ, Shang S (2013b) On discovery of gathering patterns from trajectories. In: ICDE, pp 242–253

Zheng B, Yuan NJ, Zheng K, Xie X, Sadiq SW, Zhou X (2015) Approximate keyword search in semantic trajectory database. In: ICDE, pp 975–986

Title: Multi-attribute Trajectory Data Management
Author: Jianqiu Xu
Publisher: Springer International Publishing
Book: Handbook of Big Geospatial Data
Print ISBN: 978-3-030-55461-3

Electronic ISBN: 978-3-030-55462-0

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-55462-0_9

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner