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Human-Assisted Graph Search: It’s Okay to Ask Questions Reported by Qi Liu.

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Presentation on theme: "Human-Assisted Graph Search: It’s Okay to Ask Questions Reported by Qi Liu."— Presentation transcript:

1 Human-Assisted Graph Search: It’s Okay to Ask Questions Reported by Qi Liu

2 Scenes Human Computation Crowding-sourcing service(Amazon’s Mechanical Turk)

3 An example Image classification

4 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

5 More Applications Manual Curation(insert a web into web-graph) Question: Is the item a kind of x?

6 Apps(cont.) Debugging of Workflows Question: Is the output fragment at point x wrong?

7 Apps(cont.) Filter Synthesis Question: Do you want all data items satisfying condition x to be part of the result?

8 Apps(cont.) Interactive Search Question: Do you want more results like concept x?

9 Dimensions of the problem Single/Multi (target set) Bounded/Unlimited (question set) DAG/Downward-Forest/Upward-Forest

10 Define the Problem

11 DAG property

12 Candidate Set

13 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}

14 Extending to|N|> 1

15 Goal: Picking N set

16 Single Target Node

17 Single-Bounded

18 Single-Bounded: DAG Conclusion: A NP-hard max-cover problem

19 Single-Bounded: Downward-Forest

20 Equivalence to the Partition Problem

21 Show the equivalence

22 An example

23 Candidate Set : Partition

24 Induction and Conclusion Minimum wcase(N) => the size of the largest partition that can be induced by N. Solved in PTIME!

25 Single-Bounded: Upward-Forest

26 Single-Unlimited For DAG, the question numbers vary from O(log n) to O(n)

27 Single-Unlimited: Downward-Forest

28 Single-Unlimited: Upward-Forest

29 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)

30 Experiments

31

32

33 The End


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