The task of planning an efficient itinerary has remained laborious and complicated with the bulk of online information imposing difficulty of selecting places and their visiting order. Therefore, a trip planning system generally aims to propose popular points of interests (POIs) and routes in a region structured as a POI graph. The proposed framework aims to utilize travel blogs to accumulate this information. Accordingly, existing approaches have employed frequent pattern mining to construct a POI graph that results in frequency-weighted POIs and route recommendation. The suggested model incorporates a multi-criteria weighting scheme that is contrary to the conventional POI graph. To facilitate travel decision-making, the proposed framework treats frequency measure as an initial weight and further processes blog entries to extract the opinions related to POIs and spatial information between POIs weighting nodes and edges, respectively. A final consolidated weight for each component is computed using defined functions. The contribution has significance for ordinary travelers in efficiently planning their itineraries, as well as for destination management organizations, in realizing the travelling trend and designing tourism products and strategies accordingly.
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