Travelogue Based Tourist Attractions Recommending, Trip And Route Planning System

With the rapid development of the Internet and the tourism industry, travelogues on the Internet grow rapidly in exponential order. When travelers select attractions and travel routes, travelogues have become a important reference.With diverse format and uneven quality, the huge number of travelogues often make travelers deep in it that travelers is hard to get useful information efficiently and fastly. At the same time, existing attractions recommending algorithm and tourism route planning algorithm which consider very single factor, are hard to directly apply on the massive travelogues. Based on the above considerations, this paper designs a travelogue based attractions recommending, trip and route planning system, which designs a efficient tourism route planning algorithm named MultipleGuide by efficiently mining tourist attractions from massive travelogues. MultipleGuide which takes into account satisfaction of tourist attractions, time of tourist attractions and the expense of tourist attractions all three factors, provides the most suitable route planning for travelers. To further optimize the efficiency of route planning, multiple optimization strategys are presented in this paper, which greatly speed up the speed of path searching by fast pruning.Through a lot of experiments, the method proposed in this paper can effectively extracts the tourist attractions and plans travel routes, and the effect of multiple optimization strategys is compared, which has a certain significance to the work related to travelogue based data mining.