skip to main content
10.1145/3678717.3691305acmconferencesArticle/Chapter ViewAbstractPublication PagesgisConference Proceedingsconference-collections
short-paper
Open access

Routing As a Relevance System

Published: 22 November 2024 Publication History

Abstract

Searching for directions is one of the most used features of map applications. This paper shares our vision on how Direction Services will change, with LLM-based chat assistants rapidly becoming an integral part of the underlying path search mechanism. We anticipate an influx of more complex, conversational route planning sessions, where users colloquially describe route-related preferences as if they were talking to their personal chauffeur. We envision future systems able to support asks like "avoid the East River tunnel", "take the bridge", or "find me a scenic route around the lake, oh and by the way, I'm driving the EV today". At present, popular map search engines fail in even simple, yet very natural preferences, such as 'take me from A to B via road C'. The reason is mainly twofold, inadequate query understanding and lack of mechanisms in routing to satisfy this type of preferences. The here proposed solution is a novel treatment of routing, one which casts it into an end-to-end 2-layer relevance framework. The framework is capable of performing query understanding for route queries with complex preferences and intents. It treats routes as richly annotated documents and the routing engine, in addition to performing optimization, acts (1) as a retriever of route documents that match the user intent and (2) as a ranker that ranks route candidates not just by a simple time-distance cost model, but by inferring the importance of many variables, some derived from explicitly stated preferences and others identified as relevant through data-driven methodology.

References

[1]
Ittai Abraham, Daniel Delling, Andrew V. Goldberg, and Renato F. Werneck. 2013. Alternative Routes in Road Networks. ACM J. Exp. Algorithmics (2013).
[2]
Sotiris Angelis, Konstantinos Kotis, and Dimitris Spiliotopoulos. 2021. Semantic trajectory analytics and recommender systems in cultural spaces. Big Data and Cognitive Computing 5, 4 (2021), 80.
[3]
Cambridge Vehicle Information Technology CAMVIT. 2005. Choice Routing. http://www.camvit.com/camvit-technical-english/Camvit-Choice-Routing-Explanation-english.pdf.
[4]
Ian De Felipe, Vagelis Hristidis, and Naphtali Rishe. 2008. Keyword search on spatial databases. In 2008 IEEE 24th International conference on data engineering. IEEE, 656--665.
[5]
Daniel Delling, Andrew V. Goldberg, Thomas Pajor, and Renato Fonseca F. Werneck. 2011. Customizable Route Planning. In Experimental Algorithms - 10th International Symposium, SEA 2011, Kolimpari, Chania, Crete, Greece, May 5-7, 2011. Proceedings (Lecture Notes in Computer Science, Vol. 6630). Springer, 376--387.
[6]
Julian Dibbelt, Ben Strasser, and Dorothea Wagner. 2016. Customizable Contraction Hierarchies. ACM J. Exp. Algorithmics 21 (2016).
[7]
E. W. Dijkstra. 1959. A note on two problems in connexion with graphs. Numer. Math. 1, 1 (1959).
[8]
Robert Geisberger, Peter Sanders, Dominik Schultes, and Christian Vetter. 2012. Exact Routing in Large Road Networks Using Contraction Hierarchies. Transportation science 46, 3 (2012), 388--404. https://doi.org/10.1287/trsc.1110.0401
[9]
Andrew V. Goldberg and Chris Harrelson. 2005. Computing the shortest path: A search meets graph theory. In Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms (Vancouver, British Columbia) (SODA '05). Society for Industrial and Applied Mathematics.
[10]
Jasper Huang, Chiqun Zhang, Dragomir Yankov, Maryam Mousaarab Najafabadi, and Tsheko Mutungu. 2022. Active Learning for Transformer Models in Direction Query Tagging. In Proceedings of the 30th International Conference on Advances in Geographic Information Systems (SIGSPATIAL '22). ACM.
[11]
Antonios Karatzoglou. 2022. Applying Network Kernel Density Estimation (NKDE) and Temporal Network Kernel Estimation (TNKDE) for Generating Safer Routes. In Proceedings of the 15th ACM SIGSPATIAL International Workshop on Computational Transportation Science (Seattle, Washington) (IWCTS '22). Association for Computing Machinery, New York, NY, USA.
[12]
Antonios Karatzoglou, Adrian Jablonski, and Michael Beigl. 2018. A Seq2Seq learning approach for modeling semantic trajectories and predicting the next location. In Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 528--531.
[13]
Zihan Luo, Lei Li, Mengxuan Zhang, Wen Hua, Yehong Xu, and Xiaofang Zhou. 2022. Diversified Top-k Route Planning in Road Network. In Proc. VLDB Endow.
[14]
Ronaldo dos Santos Mello, Vania Bogorny, Luis Otavio Alvares, Luiz Henrique Zambom Santana, Carlos Andres Ferrero, Angelo Augusto Frozza, Geomar Andre Schreiner, and Chiara Renso. 2019. MASTER: A multiple aspectview on trajectories. Transactions in GIS 23, 4 (2019), 805--822.
[15]
Giacomo Nannicini, Daniel Delling, Dominik Schultes, and Leo Liberti. 2012. Bidirectional A* Search on Time-Dependent Road Networks. Netw. (2012).
[16]
Ben Strasser, Dorothea Wagner, and Tim Zeitz. 2021. Space-Efficient, Fast and Exact Routing in Time-Dependent Road Networks. Algorithms 14, 3 (2021).
[17]
Josh JC Ying, WC Lee, Tz-C Weng, and Vincent S Tseng. 2011. Semantic trajectory mining for location prediction. In Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 34--43.
[18]
Chiqun Zhang, Antonios Karatzoglou, Helen Craig, and Dragomir Yankov. 2023. Map GPT Playground: Smart Locations and Routes with GPT. In Proceedings of the 31th International Conference on Advances in Geographic Information Systems. ACM.
[19]
Bolong Zheng, Lei Bi, Juan Cao, Hua Chai, Jun Fang, Lu Chen, Yunjun Gao, Xiaofang Zhou, and Christian S Jensen. 2021. Speaknav: Voice-based route description language understanding for template-driven path search. Proceedings of the VLDB Endowment 14, 12 (2021), 3056--3068.
[20]
Bolong Zheng, Nicholas Jing Yuan, Kai Zheng, Xing Xie, Shazia Sadiq, and Xiaofang Zhou. 2015. Approximate keyword search in semantic trajectory database. In 2015 IEEE 31st International Conference on Data Engineering. IEEE, 975--986.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
SIGSPATIAL '24: Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems
October 2024
743 pages
This work is licensed under a Creative Commons Attribution International 4.0 License.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 November 2024

Check for updates

Author Tags

  1. Optimal Path
  2. Query Understanding
  3. Ranking
  4. Retrieval
  5. Routing

Qualifiers

  • Short-paper
  • Research
  • Refereed limited

Conference

SIGSPATIAL '24
Sponsor:

Acceptance Rates

SIGSPATIAL '24 Paper Acceptance Rate 37 of 122 submissions, 30%;
Overall Acceptance Rate 257 of 1,238 submissions, 21%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 46
    Total Downloads
  • Downloads (Last 12 months)46
  • Downloads (Last 6 weeks)36
Reflects downloads up to 14 Jan 2025

Other Metrics

Citations

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media