1 / 21

Location Clustering

Location Clustering. Peter Kamm Marcel Flores. The Data Set. Sessions Contains a collection of connections over the course of a week User ID, Start time, stop time, Tower ID 25 million lines!. ...a little more. A tower location mapping Tower ID, Longitude, Latitude, Zip Code

philip-mccarthy
Télécharger la présentation

Location Clustering

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Location Clustering Peter Kamm Marcel Flores

  2. The Data Set • Sessions • Contains a collection of connections over the course of a week • User ID, Start time, stop time, Tower ID • 25 million lines!

  3. ...a little more • A tower location mapping • Tower ID, Longitude, Latitude, Zip Code • Allows us to map to a real world location • Data set is not complete • There are many towers we do not have a location for

  4. Applications • Load balancing on the cell-phone networks themselves • Social Networking • Integrate online social networks with the real world • Accounts for mobility and usage patterns

  5. Analysis • See which locations are active at what times • Where do people congregate? • How strongly do they congregate? • Does the locations affect their usage • Connection Duration • How does this map out into the physical world?

  6. Day and Night Hotspots • Now uses a proper qualitative metric • Looks at all ratio of day to night (or night to day, depending on which is larger) • Rejected locations with <100 day or night sessions • Gives us a number >1 to rank strength of location • Daytime is defined as 4am to 4pm • Day has more “very strong” hotspots

  7. Day and Night Ranks

  8. Day - 4,479 total Strength Distribution Night - 10,812 total

  9. Day and Night Plots

  10. Day/Night Durations

  11. Day Avg Durations

  12. Durations • Day/night hotspots tend to exhibit similar patterns of usage • Longest connections during morning/evening commute • Urban towers get longer connections in mornings, residential neighborhoods get longer connections in evenings

  13. Physical Locations • Have to be done by hand, smaller sample • Incomplete, do not have locations for all towers • For the highest ranked locations • Sadly the top 4 shown previously not in location data set! • In fact, none of the high-ratio day or night spots appear (until down to a ratio of <2)!

  14. Some Locations… • Tower 79 - Night Tower, 1.255 ratio • Located in Englewood • Residential • South Chicago • Not very strong ratio

  15. Tracing a User • Turns out, the data set was (maybe) rich enough to provide information on a per user level! • Followed the first 5000 users in the data set, ranked them based on activity • Considered the busiest (by hand) • Compared to day/night ratio of each location

  16. Tracing a User: Results • User 1: • Busiest at tower 24 (20,729) • Night tower with a 2.339 ratioBut the user accounts for over 99% of the tower traffic! • 2nd Busiest at tower 1197 (3,660) • Night tower with a 1.528 ratio • Again accounts for 99% of traffic!

  17. Tracing a User: Results • User 5: • Busiest at tower 258 (7,449) • Night tower with a 1.711 ratio (75% of traffic!) • No location data • 2nd Busiest at tower 309 (5,773) • Night tower with a 1.765 ratio (only 60%…) • Residential, Longview, Washington

  18. Tracing a User: Results • Had to go to user 113 to get a more reasonable user • Busiest at tower 100 (1,602) • Night tower at 1.207 ratio • Not an unreasonable amount of traffic • Solon, Iowa • Second busiest at 5045 (602) • Night tower at 2.004

  19. Single-user Durations

  20. Hotspots • Looking at certain user traces, seemed that certain users seemed to use the busiest towers the most • So are the busiest towers really seeing a lot of users, or a few very busy users? • Analyzed the numbers of unique users that a tower sees in a day

  21. Unique User Data • Count how many users a specific tower sees over the duration • Allows us to give an alternate ranking of the tower traffic • Easily ignore points where a single user accounts for the majority of a towers traffic • Actual data is forthcoming…

More Related