Point of Interest Assisted Dynamic Travel Route Suggestion Model using Keyword Representation Logic

Abstract

Check-in data and photographs from journeys may be simply shared via social media. In light of the massive amount of social media data on user mobility, this work attempts to find travel experiences that might help plan a trip. When it comes to vacation planning, people always have a list of things they want to look for. As an alternative to limiting search options to places, activities, or time periods, arbitrary text descriptions are regarded as keywords that describe the individual demands of each user. It's also necessary to provide a wide variety of suggestions about how to go around. Previous research has focused on analyzing check-in data to identify and rank the most popular routes. According to us, additional POI characteristics should be retrieved in order to match the need for autonomous trip organizing. For the Keyword Representation Logic with Travel Route Suggestion Model (KRLTRSM) suggested in this research, knowledge extraction from users' historical mobility records as well as social interactions is used to give efficient keyword representation logic for search engines to employ (KRLTRSM). In order to effectively match query keywords with POI-related tags, we've created a KRLTRSM model explicitly. The method for reconstructing routes provided route candidates that matched the requirements specified. In order to provide acceptable query replies, representative Skyline concepts, or Skyline routes that best reflect the trade-offs between various POI qualities, are investigated. As shown by the experiment findings, these methodologies outperform existing state-of-the-art research based on extensive testing on real location-based social network datasets.