• Find longest path
• Display ad for specific user
• Compare between users' frequently visited websites
• Display ads towards most-fit user (e.g. a user who visits social media versus someone who visits news websites will get more social ads)

Our graphs were directed graphs due to counting only the website visits from different users as opposed to one user visiting a website multiple times. This would keep track of the diversity of visitors and counts the population occupying a website. For example, if the graphs were cyclic, then a user would be able to visit a website 300 times which would not be a true population count.

Hamilthonian Path

Due to the nature of our graphs being directed and acyclic, the topological sort handles the visit of each vertex already. Thus, the Hamilthonian theorem is resolved within our graphs with no need to track the visit of each vertex via boolean functions.

• Took out i+1
• Made array size 7 [0-6]
• First index is always 0 but somehow shuffler skips 0 MAGIC

Implicit conversion loses integer precision: 'size_type' (aka 'unsigned long') to 'int'
line 19 in Hash.cpp

Completed

• Creating 2 categories, with 4 files total
• 1 file for loading ads into Hash table
• Predetermined direction of nodes
• Layout of project drawn out in Draw.io
• Conflict where root node pointed to another node in a cycle (Not acyclic)

Randomizing

• Weights are more important
• Randomizing for user visiting a certain website given the direction of node to adjacent nodes

Directed Acyclic Graph
Topological Sorting
Hamilthonian Path

Weight is apparently out of bounds (i[10]) when the graph vertex bound is 6. How to compress values such as facebook which are multiple into that size of 6 e.g.:

• Google Adsense
• Adwords
• Carbon