Interactive itinerary planning

Planning an itinerary when traveling to a city involves substantial effort in choosing Points-of-Interest (POIs), deciding in which order to visit them, and accounting for the time it takes to visit each POI and transit between them. Several online services address different aspects of itinerary planning but none of them provides an interactive interface where users give feedbacks and iteratively construct their itineraries based on personal interests and time budget. In this paper, we formalize interactive itinerary planning as an iterative process where, at each step: (1) the user provides feedback on POIs selected by the system, (2) the system recommends the best itineraries based on all feedback so far, and (3) the system further selects a new set of POIs, with optimal utility, to solicit feedback for, at the next step. This iterative process stops when the user is satisfied with the recommended itinerary. We show that computing an itinerary is NP-complete even for simple itinerary scoring functions, and that POI selection is NP-complete. We develop heuristics and optimizations for a specific case where the score of an itinerary is proportional to the number of desired POIs it contains. Our extensive experiments show that our algorithms are efficient and return high quality itineraries.

[1]  Adrian Popescu,et al.  Deducing trip related information from flickr , 2009, WWW '09.

[2]  Keith Cheverst,et al.  Developing a context-aware electronic tourist guide: some issues and experiences , 2000, CHI.

[3]  Cong Yu,et al.  Automatic construction of travel itineraries using social breadcrumbs , 2010, HT '10.

[4]  Fabien Girardin Aspects of implicit and explicit human interactions with ubiquitous geographic information , 2009 .

[5]  David B. Leake,et al.  Mining Large-Scale Knowledge Sources for Case Adaptation Knowledge , 2007, ICCBR.

[6]  Mor Naaman,et al.  World explorer: visualizing aggregate data from unstructured text in geo-referenced collections , 2007, JCDL '07.

[7]  J. F. Pierce,et al.  ON THE TRUCK DISPATCHING PROBLEM , 1971 .

[8]  Chandra Chekuri,et al.  Improved algorithms for orienteering and related problems , 2008, SODA '08.

[9]  Ming-Syan Chen,et al.  Recommending personalized scenic itinerarywith geo-tagged photos , 2008, 2008 IEEE International Conference on Multimedia and Expo.

[10]  Ke Chen,et al.  The Euclidean Orienteering Problem Revisited , 2008, SIAM J. Comput..

[11]  David B. Leake,et al.  Knowledge Planning and Learned Personalization for Web-Based Case Adaptation , 2008, ECCBR.

[12]  Ronald L. Rivest,et al.  Introduction to Algorithms , 1990 .

[13]  Yehoshua Sagiv,et al.  Interactive route search in the presence of order constraints , 2010, Proc. VLDB Endow..

[14]  David R. Karger,et al.  Approximation Algorithms for Orienteering and Discounted-Reward TSP , 2007, SIAM J. Comput..

[15]  Mor Naaman,et al.  Towards automatic extraction of event and place semantics from flickr tags , 2007, SIGIR.

[16]  David R. Karger,et al.  Approximation algorithms for orienteering and discounted-reward TSP , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..

[17]  Jon M. Kleinberg,et al.  Mapping the world's photos , 2009, WWW '09.

[18]  Philip Kilby,et al.  An Automated Itinerary Planning System for Holiday Travel , 2003, J. Inf. Technol. Tour..

[19]  Kevin Li,et al.  Faceted metadata for image search and browsing , 2003, CHI '03.

[20]  Ronald L. Rivest,et al.  Introduction to Algorithms, Second Edition , 2001 .

[21]  Liliana Ardissono,et al.  Intrigue: Personalized recommendation of tourist attractions for desktop and hand held devices , 2003, Appl. Artif. Intell..

[22]  Moni Naor,et al.  Optimal aggregation algorithms for middleware , 2001, PODS '01.

[23]  Cong Yu,et al.  Constructing and exploring composite items , 2010, SIGMOD Conference.