RoundTripRank: Graph-based Proximity with Importance and Specificity Yuan Fang 1,2

Kevin C.-C. Chang 1,2

Hady W. Lauw 3

1

University of Illinois at Urbana-Champaign, USA 2 Advanced Digital Sciences Center, Singapore 3 Singapore Management University, Singapore

arise.adsc.com.sg

Problem: Proximity Ranking on the Graph Citation network

Query log graph

Example Applications • Find expert reviewers for a paper • Find matching venues for some keywords

Social network

• Find relevant pages for a search phrase • Find similar search phrases of a given phrase

Observations: Importance & Specificity and Their Flexible Trade-offs Observation 1:

background study?

Most tasks require both importance and specificity.

report prelim findings?

Observation 2:

important

The desirable trade-off varies from task to task.

specific balanced

Reasonable, but what’s missing?

Challenge 1: How to unify

Challenge 2: How to

Challenge 3: How to compute

importance & specificity?

customize their trade-offs?

the proximity efficiently?

Citation analogy for importance/specificity

Hybrid surfers 𝛀

Customization

RoundTripRank

Divide and conquer

RoundTripRank+

Finding 1: Both importance &

Finding 2: Customizable trade-

Finding 3: Our computational

specificity are needed.

offs are needed.

model enables efficient ranking.

RoundTripRank vs. mono-sensed proximity

RoundTripRank+ vs. dual-sensed proximity

RoundTripRank

0.4

F-Rank/PPR

0.3

T-Rank

0.2

SimRank AdamicAdar

0.1 NDCG@5 NDCG@10 NDCG@20

RoundTripRank+

0.55

TCommute

0.50

ObjSqrtInv Harmonic

0.45

Arithmetic

0.40

NDCG@5 NDCG@10 NDCG@20

8 Growth factor

0.5

Scalability

1E+5

0.60

1E+4 Time (ms)

0.6

Efficiency

1E+3 1E+2 1E+1 1E+0 Naïve Top-K

6

Snapshot Query time

4 2

0 1994 1998 2002 2006 2010 Timestamp (year)

RoundTripRank: Graph-based Proximity with ...

Citation network. Social network. Query log graph important specific balanced. 0.1. 0.2. 0.3. 0.4. 0.5. 0.6. NDCG@5 NDCG@10 NDCG@20. RoundTripRank.

1MB Sizes 4 Downloads 308 Views

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