Main Reference PaperPersonalized Travel Sequence Recommendation on Multi-Source Big Social Media, IEEE Transactions on Big Data, May 2016 [J2EE/Hadoop].
  • This work proposes a learning algorithm called Topical Package Model which learns users travel preferences from text descriptions associated with geo-tagged photos. Then optimized top ranked famous travel sequences are recommended according to social similar users travel records.

+ Description
  • This work proposes a learning algorithm called Topical Package Model which learns users travel preferences from text descriptions associated with geo-tagged photos. Then optimized top ranked famous travel sequences are recommended according to social similar users travel records.

  • To achieve the accuracy of recommendation.

  • To recommended the POI travel sequence of time and session.

  • To achieve the scalability.

+ Aim & Objectives
  • To achieve the accuracy of recommendation.

  • To recommended the POI travel sequence of time and session.

  • To achieve the scalability.

  • This work contributes time aware POI recommendation, which aims to return a set of POIs for a user to visit at a specified time in a day. During recommendation mine the temporal behaviors of users by analyzing their historical check ins, and make use of the mined temporal behaviors for time aware POI recommendations.

+ Contribution
  • This work contributes time aware POI recommendation, which aims to return a set of POIs for a user to visit at a specified time in a day. During recommendation mine the temporal behaviors of users by analyzing their historical check ins, and make use of the mined temporal behaviors for time aware POI recommendations.

  • Java JDK 1.8, Hadoop 1.2.1, MySQL 5.5.40

  • Netbeans 8.0.1, J2EE, Hadoop

+ Software Tools & Technologies
  • Java JDK 1.8, Hadoop 1.2.1, MySQL 5.5.40

  • Netbeans 8.0.1, J2EE, Hadoop

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-Depending on the complexity of the project and requirements.

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