Human-Assisted Graph Search: It’s Okay to Ask Questions
Reported by Qi Liu
Scenes
• Human Computation• Crowding-sourcing service(Amazon’s
Mechanical Turk)
An example
• Image classification
Terminology of the Problem
• HumanGS: abbreviation for human-assisted graph search
• Taxonomy: DAG(directed acyclic graph)• Category: Node• Question: Reachability• Tricks: Not leaves, Not root, Just middle!• Challenge: High Latency
More Applications
• Manual Curation(insert a web into web-graph)• Question: Is the item a kind of x?
Apps(cont.)
• Debugging of Workflows• Question: Is the outputfragment at point x wrong?
Apps(cont.)
• Filter Synthesis• Question: Do youwant all data items satisfying conditionx to be part of theresult?
Apps(cont.)
• Interactive Search• Question: Do you want more results like
concept x?
Dimensions of the problem
• Single/Multi (target set)• Bounded/Unlimited (question set)• DAG/Downward-Forest/Upward-Forest
Define the Problem
DAG property
Candidate Set
An Example
Q(nissan,maxima)=yes=>
Cand(nissan,maxima)={nissan,maxima,sentra}Q(mercedes,maxima)=no
=>Cand(mercedes,maxima)=V/{mercedes}
Q(car,maxima)=yes=>
Cand(car,maxima)=V/{vehicle}
Extending to|N|> 1
Goal: Picking N set
Single Target Node
Single-Bounded
Single-Bounded: DAG
Conclusion: A NP-hard max-cover problem
Single-Bounded: Downward-Forest
Equivalence to the Partition Problem
Show the equivalence
An example
Candidate Set : Partition
Induction and Conclusion
• Minimum wcase(N) => the size of the largest partition that can be induced by N.
• Solved in PTIME!
Single-Bounded: Upward-Forest
Single-Unlimited
• For DAG, the question numbers vary from O(log n) to O(n)
Single-Unlimited: Downward-Forest
Single-Unlimited: Upward-Forest
Multiple Target Nodes
• Multi-Bounded: DAG• Lower-bound: NP-hard in n and k• Upper-bound: • Multi-Bounded: Downward/Upward-Forest– DP algorithm: O(k^2*n*6)
Experiments
The End
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