Using Collective Intelligence to Generate Trend-based Travel Recommendations

Sabine Schlick, Isabella Eigner, Alex Fechner

2015

Abstract

Trips are multifaceted, complex products which cannot be tested in advance due to their geographical distance. Hence, making a travel decision people often ask others for advice. This leads to an increasing importance of communities. Within communities people share their experiences, which results in new, more extensive knowledge beyond the individual knowledge of each member. The objective of this paper is to use this knowledge by developing an algorithm that automatically generates trend-based travel recommendations. Based on the travel experiences of the community members, interesting travel areas are identified. Five key figures to evaluate these areas according to general criteria and the users’ individual preferences are developed. The algorithm allows to generate recommendations for the whole community and not only for highly active members, resulting in a high coverage. A study conducted within an online travel community shows that automatically generated, trend-based trip recommendations are rated better than user-generated recommendations.

References

  1. Adomavicius, G., and Tuzhilin, A. “Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions.” IEEE Transactions on Knowledge and Data Engineering 17, no. 6 (2005): 734-749.
  2. Bächle, Michael. “Ökonomische Perspektiven des Web 2.0- Open Innovation, Social Commerce und Enterprise 2.0.” WIRTSCHAFTSINFORMATIK 50, no. 2 (2008): 129-132.
  3. Baraglia, Ranieri, Frattari, Claudio, Muntean, Cristina Ioana, Nardini, Franco Maria, and Silvestri, Fabrizio. “RecTour: A Recommender System for Tourists.” In 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). Piscataway: IEEE, 2012.
  4. Birant, Derya, and Kut, Alp. “ST-DBSCAN: An algorithm for clustering spatial-temporal data.” Data & Knowledge Engineering 60, no. 1 (2007): 208-221.
  5. Bortz, Jürgen, and Schuster, Christof. Statistik für Humanund Sozialwissenschaftler. 7th ed. Berlin: Springer, 2010.
  6. Burke, Robin. “Hybrid Recommender Systems: Survey and Experiments.” User Modeling and User-Adapted Interaction, November 2002, pp. 331-370.
  7. Ester, Martin, Kriegel, Hans-Peter, Sander, Jörg, and Xu, Xiaowei. “A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise.” In KDD-1996: Proceedings of the 2nd international conference on knowledge discovery and data mining: AAAI Press, 1996.
  8. Frers, Uwe. “Facebook-Applications im Tourismus - Casestudy „Gedankenreise“ des Reiseportals TripsByTips.” In Social Web im Tourismus: StrategienKonzepte- Einsatzfelder, edited by Daniel Amersdorffer, Florian Bauhuber, Roman Egger and Jens Oellrich. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010.
  9. Gruber, Tom. “Collective knowledge systems: Where the Social Web meets the Semantic Web.” Web Semantics: Science, Services and Agents on the World Wide Web 6, no. 1 (2008): 4-13.
  10. Hevner, Alan R., March, Salvatore T., Park, Jinsoo, and Ram, Sudha. “Design Science in Information Systems Research.” MIS Quarterly 28 (2004): 75-105.
  11. Hwang, Yeong-Hyeon, Gretzel, Ulrike, and Fesenmaier, Daniel R. “Behavioral Foundations for Human-Centric Travel Decision-Aid Systems.” In Information and Communication Technologies in Tourism 2002: Proceedings of the International Conference in Innsbruck, Austria, 2002. Vienna: Springer Vienna, 2002.
  12. Jannach, Dietmar. Recommender systems: An introduction. New York: Cambridge University Press, 2011.
  13. Magno, Terence, and Sable, Carl. “A Comparison of Signal-Based Music Recommendation to Genre Labels, Collaborative Filtering, Musicological Analysis, Human Recommendation, and Random Baseline.” In ISMIR 2008: Proceedings of the 9th International Conference of Music Information Retrieval, edited by Juan Pablo Bello, Elaine Chew and Douglas Turnbull. Philadelphia Drexel University, 2008.
  14. Malone, Thomas W., Laubacher, Robert, and Dellarocas, Chrysanthoas. “Harnessing Crowds: Mapping the Genome of Collective Intelligence.” MIT Sloan Research Paper No. 4732-09, 2009.
  15. Massa, Paolo, and Avesani, Paolo. “Trust-aware recommender systems.” In RecSys 7807: Proceedings of the 2007 ACM Conference on Recommender Systems: Minneapolis, MN, USA, October 19-20, 2007. New York: Association for Computing Machinery, 2007.
  16. Meo, Pasquale de, Ferrara, Emilio, Fiumara, Giacomo, and Provetti, Alessandro. “Improving recommendation quality by merging collaborative filtering and social relationships.” In 11th International Conference on Intelligent Systems Design and Applications (ISDA), 2011: 22 - 24 November 2011, Córdoba, Spain ; [including workshop papers], edited by Sebastián Ventura. Piscataway, NJ: IEEE, 2011.
  17. Monreale, Anna, Pinelli, Fabio, Trasarti, Roberto, and Giannotti, Fosca. “WhereNext: a location predictor on trajectory pattern mining.” In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Paris, France, 2009.
  18. Montavont, Julien, and Noel, Thomas. “IEEE 802.11 Handovers Assisted by GPS Information.” In 2nd IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, 2006: IEEE WiMob 2006: June 19-21, 2006: Montréal, Canada. Piscataway, N. J: IEEE, 2006.
  19. Nitschke, Martin. Geometrie: Anwendungsbezogene Grundlagen und Beispiele für Ingenieure. 2nd ed. München: Hanser, 2014.
  20. Prestipino, Marco, and Schwabe, Gerhard. “TourismusCommunities als Informationssysteme.” In Wirtschaftsinformatik 2005: EEconomy, eGovernment, eSociety, edited by Otto K. Ferstl, Elmar J. Sinz, Sven Eckert and Tilman Isselhorst. Heidelberg: PhysicaVerlag, 2005.
  21. Ricci, Francesco, Fesenmaier, Daniel R., Mirzadeh, Nader, Rumetshofer, Hildegard, Schaumlechner, Erwin, Venturini, Adriano, Wöber, Karl W., and Zins, Andreas H. “DieToRecs: A Case-based Travel Advisory System.” In Destination recommendation systems: Behavioural foundations and applications, edited by Daniel R. Fesenmaier, Hannes Werthner and Karl W. Wöber. Wallingford [u.a]: CABI, 2006.
  22. Sebastia, Laura, Garcia, Inma, Onaindia, Eva, and Guzman, Cesar. “e-Tourism: a Tourist Recommendation and Planning Application.” International Journal on Artificial Intelligence Tools 18, no. 5 (2009): 717-738.
  23. Sinnott, R. W. “Virtues of the Haversine.” Sky and Telescope 68, no. 2 (1984): 159.
  24. Smyth, Barry. “Case-Based Recommendation.” In The adaptive web: Methods and strategies of web personalization, edited by Peter Brusilovsky, Alfred Kobsa and Wolfgang Nejdl. Berlin, New York: Springer, 2007.
  25. Tung, Hung-Wen, and Soo, Von-Wun. “A personalized restaurant recommender agent for mobile E-service.” In 2004 IEEE International Conference on e-Technology, e-Commerce, and e-Services (EEE 04). Los Alamitos, Piscataway: IEEE Computer Society Press; IEEE [Distributor], 2004.
  26. Wallace, Manolis, Maglogiannis, Ilias, Karpouzis, Kostas, Kormentzas, George, and Kollias, Stefanos. “Intelligent one-stop-shop travel recommendations using an adaptive neural network and clustering of history.” Information Technology & Tourism 6, no. 3 (2004): 181-193.
  27. Yoon, Hyoseok, Zheng, Yu, Xie, Xing, and Woo, Woontack. “Social Itinerary Recommendation from User-Generated Digital Trails.” Personal and Ubiquitous Computing 16, no. 5 (2012): 469-484.
  28. Zins, Andreas H., and Grabler, Klaus. “Destination Recommendations Based on Travel Decision Styles.” In Destination recommendation systems: Behavioural foundations and applications, edited by Daniel R. Fesenmaier, Hannes Werthner and Karl W. Wöber. Wallingford [u.a]: CABI, 2006.
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Paper Citation


in Harvard Style

Schlick S., Eigner I. and Fechner A. (2015). Using Collective Intelligence to Generate Trend-based Travel Recommendations . In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015) ISBN 978-989-758-158-8, pages 177-185. DOI: 10.5220/0005582201770185


in Bibtex Style

@conference{kdir15,
author={Sabine Schlick and Isabella Eigner and Alex Fechner},
title={Using Collective Intelligence to Generate Trend-based Travel Recommendations},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)},
year={2015},
pages={177-185},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005582201770185},
isbn={978-989-758-158-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)
TI - Using Collective Intelligence to Generate Trend-based Travel Recommendations
SN - 978-989-758-158-8
AU - Schlick S.
AU - Eigner I.
AU - Fechner A.
PY - 2015
SP - 177
EP - 185
DO - 10.5220/0005582201770185