View source for Snap inc. (20240331010). SCALABLE ONLINE PLACE RECOMMENDATION simplified abstract

=SCALABLE ONLINE PLACE RECOMMENDATION=


==Organization Name==

[[:Category:snap inc.|snap inc.]]


[[Category:snap inc.]]

==Inventor(s)==

[[:Category:Christopher Shughrue of Canaan NY (US)|Christopher Shughrue of Canaan NY (US)]][[Category:Christopher Shughrue of Canaan NY (US)]]

==SCALABLE ONLINE PLACE RECOMMENDATION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240331010 titled 'SCALABLE ONLINE PLACE RECOMMENDATION

The patent application describes a system and method for accessing user location data and place data on a computing device, including check-in data and a check-in location distribution parameter.

* The system computes a relevance score for each place based on user location data and check-in data, ranks the places, and displays the ranking on the computing device.
* Relevance scores can be based on distance between the user location and each place, or the count of place-associated check-ins over time.
* The check-in location distribution parameter can be a Gaussian shape parameter.

### Potential Applications:
This technology could be used in location-based services, social networking apps, and personalized recommendations for users based on their location and preferences.

### Problems Solved:
This system helps users discover relevant places based on their location and check-in data, improving their overall experience and convenience.

### Benefits:
Users can easily find places of interest nearby, receive personalized recommendations, and make informed decisions on where to go based on relevance scores.

### Commercial Applications:
"Location-Based Recommendation System for Mobile Apps: Enhancing User Experience and Engagement"

### Prior Art:
Prior art related to this technology may include research on location-based services, recommendation systems, and user behavior analysis in mobile applications.

### Frequently Updated Research:
Stay updated on advancements in location-based services, user data privacy regulations, and machine learning algorithms for personalized recommendations.

#### Questions about Location-Based Recommendation System:
1. How does this system ensure user data privacy while accessing location information?
2. What are the potential challenges in implementing this technology in real-world applications?


==Original Abstract Submitted==

system and method for accessing, on a computing device, user location data and place data for each place of a plurality of places, the place data including check-in data such as locations of place-associated check-ins, and a check-in location distribution parameter computed based on the locations of place-associated check-ins. the system further computes a relevance score for each place of the plurality of places based on the user location data and the check-in data, ranks the plurality of places based on the respective relevance scores, and displays the ranking of the plurality of places at the computing device. computing the relevance score can be further based on a distance between the user location and each place, or a count of place-associated check-ins over a predetermined period of time. the check-in location distribution parameter can be a gaussian shape parameter.



[[Category:G06Q30/0601]]
[[Category:G06Q10/02]]
[[Category:CPC_G06Q30/0631]]