Project - SERRATE -- Sustainable Rural Tourism Engine

Overview

By integrating data from different sources and sectors, SERRATE will enable an automated workflow: collect social media posts about a region, extract data features from these, match posts with an extendable knowledge base of stories, and reply on the same medium with highlighted stories that match the interest of the user. Manual human intervention will also be facilitated so that social media managers can control and tune the user/tourist experience.

The project builds upon Tellit, IN2’s storytelling and social media aggregation platform for tourism and events. Thanks to SERRATE, Tellit will be extended with more targeted features for the tourism vertical market segment by extracting more accurate user profiles and by a story recommendation service to increase tourist user engagement and interaction.

SERRATE uses several data sources: real-time social media posts shared, searched keywords, point of interest data, geo-location data, promotional stories from local actors and destination management organisation. AI technologies will be used to enrich the data and extract additional keywords, sentiments and topics.

SERRATE helps DMOs to effectively direct the flow of tourists from hotspots to less known rural areas by:

• integrating cross-domain data sources like real-time sharing of posts on social media around the region (e.g. Valencia) with info about the specific points of interests, search keywords; in order to
• extract sentiment, keywords, topics using AI (e.g. NLP, image recognition) technologies from these posts,
• matching them with a curated and extendable storytelling knowledge base about activities (outdoor / nature, culture, gastronomy, actual local events, e.g. festivals)

Visitors/tourists login with Twitter and take a short quiz to select what best fits their preferences. Accordingly relevant trip recommendations and activities are presented based on an index that shows how sustainable is a visit to the suggested places at the current moment.