Building Software Agents for Planning, Monitoring, and Optimizing Travel

Planning and executing a trip requires assembling a wide variety of interacting information from a large number of sources, including information on flight schedules and prices, hotel locations and reviews, ground transportation options, weather conditions, airport delays, flight cancellations, etc. Much of this information is now available on the Internet and it can be used to enable travelers to better plan and execute their trips. This paper describes the use of software agents for extracting, integrating and mining online data sources to improve the ability to plan, monitor, and optimize travel. These agents can dynamically extract data from online travel sources, integrate this data to support interactive travel planning, continuously monitor all aspects of a trip to ensure a trip goes smoothly, and exploit data mining to make predictions that can either save a traveler money or improve the likelihood of a successful trip.

[1]  Chun-Nan Hsu,et al.  Generating Finite-State Transducers for Semi-Structured Data Extraction from the Web , 1998, Inf. Syst..

[2]  Oren Etzioni,et al.  Learning to Understand Information on the Internet: An Example-Based Approach , 1997, Journal of Intelligent Information Systems.

[3]  Jean Oh,et al.  Mixed-initiative, multi-source information assistants , 2001, WWW '01.

[4]  Craig A. Knoblock,et al.  Automatic Data Extraction from Lists and Tables in Web Sources , 2001 .

[5]  Oren Etzioni,et al.  To Buy or Not to Buy: Mining Airline Fare Data to Minimize Ticket Purchase Price , 2003 .

[6]  Valter Crescenzi,et al.  RoadRunner: Towards Automatic Data Extraction from Large Web Sites , 2001, VLDB.

[7]  Craig A. Knoblock.  Deploying Information Agents on the Web , 2003, IJCAI.

[8]  Craig A. Knoblock,et al.  Selective Sampling with Redundant Views , 2000, AAAI/IAAI.

[9]  Jean Oh,et al.  Electric Elves: Applying Agent Technology to Support Human Organizations , 2001, IAAI.

[10]  Craig A. Knoblock,et al.  Speculative Execution for Information Gathering Plans , 2002, AIPS.

[11]  Jean Oh,et al.  Getting from here to there: interactive planning and agent execution for optimizing travel , 2002, AAAI/IAAI.

[12]  David H. Wolpert,et al.  Stacked generalization , 1992, Neural Networks.

[13]  Boi Faltings,et al.  SmartClients: Constraint Satisfaction as a Paradigm for Scaleable Intelligent Information Systems , 2004, Constraints.

[14]  Oren Etzioni,et al.  To buy or not to buy: mining airfare data to minimize ticket purchase price , 2003, KDD '03.

[15]  Alon Y. Halevy,et al.  An XML query engine for network-bound data , 2002, The VLDB Journal.

[16]  Craig A. Knoblock,et al.  Hierarchical Wrapper Induction for Semistructured Information Sources , 2004, Autonomous Agents and Multi-Agent Systems.

[17]  Craig A. Knoblock,et al.  Learning Value Predictors for the Speculative Execution of Information Gathering Plans , 2003, IJCAI.

[18]  Craig A. Knoblock,et al.  Wrapper Maintenance: A Machine Learning Approach , 2011, J. Artif. Intell. Res..

[19]  Nicholas Kushmerick,et al.  Wrapper Induction for Information Extraction , 1997, IJCAI.