3D head reconstruction solution
Our client is a creative design agency that provides branding, advertising, graphic design, and virtual modeling services for individuals and corporate customers. The agency has its own in-house souvenir production.
We are working on a geosocial networking application that leverages geolocation and user time data to provide personalized recommendations for nearby locations, points of interest, events, and translation to needed language. The app aims to enhance user experiences by offering relevant suggestions tailored to their current location and time, fostering meaningful connections and engagement.
Geosocial networking apps are a relatively new type of social apps. The most popular players on the market are Yelp, Facebook Places, and Foursquare. These apps allow users to share their locations as well as find recommendations for locations, or ‘venues’.
Sharing our location on online social networks has great advantages: it can help us find our way, pick restaurants and shops, and even locate nearby friends and other people within the selected radius. Our client wanted to create a unique geosocial networking solution powered by AI for the local market.
The required recommendation system has to use:
– Computer Vision to analyze images;
– NLP technology to analyze chat and image captions, and automatically pinpoint topics of interest, locations, dates and time for proper advice;
– Recognition of voice commands in several languages; support of topic modeling of social messages, as well as syntactic text simplification of complex sentences in the information repository structured as a graph.
Geosocial networking apps are a relatively new type of social apps. The most popular players on the market are Yelp, Facebook Places, and Foursquare. These apps allow users to share their locations as well as find recommendations for locations or ‘venues’.
Our client wanted to create a unique geosocial networking solution powered by AI for the local market.
– The client’s main idea was to change a commonly-used approach to social media posting and social networking apps, add voice and language recognition and create a unique recommendation system;
– Our client was looking for a development team with experience in Machine Learning;
– Our client wanted to start as fast as possible and create a working prototype of a recommendation model for his investors.
Our team was in charge of the project, starting with the discovery phase and POC, and finishing with the development of the app prototype, adding new features and product support.
– This social networking app is organized according to the principle of calendar flow. It is formed depending on the time and location of the app user. The content is broadcast from the place where the user is located and connected to the Internet.
– Social communication is possible through the internal chat platform with the functionality to post photos and video files, and comment posts of other users.
– To cope with a large amount of user data, our ML experts have built a knowledge graph of the social network. This custom database helps save and structure different facts given by users for further use in communication and recommendations.
– The app automatically recognizes the event, date, time, and location of the user thanks to Named Entity Recognition (“What”, “Where”, “When”) or voice assistant powered by ChatGPT. Based on this information, the user receives a list of recommendations, answers to their questions, and even relevant translations of needed sights, and phrases.
The geosocial networking project is very interesting and technically challenging, and that’s the greatest appeal of it! We have tested a lot of models and technologies to solve certain problems. The most difficult part of the project, probably, was that at the start of the project, we did not have enough real data. The most memorable thing for me was the creation of a knowledge graph for the social network. The task turned out to be very multifaceted and included many other subtasks.