Location Prediction on Location Based Social Network Lau Chun Ki.

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Presentation transcript:

Location Prediction on Location Based Social Network Lau Chun Ki

Outline 1. Location 3: How Users Share and Respond to Location-Based Data on Social Networking Sites (Jonathan Chang, Eric Sun) 2. Addressing the Cold-Start Problem in Location Recommendation Using Geo-Social Correlations (Huiji Gao, Jilliang Tang, Huan Liu)

Location-Based Social Network

Location 3: How Users Share and Respond to Location-Based Data on Social Networking Sites 1. Location 2. Response 3. Friendship

Major Findings

What About a New Place? Location Prediction User’s Previous Check-in Record Friends Check-in Record

COLD-START PROBLEM

Addressing the Cold-Start Problem in Location Recommendation Using Geo- Social Correlations gSCorr Geo-social Circles –Geographic factor (D: Distant) –Social factor (F: Friends)

Geo-social Circles

Location Recommendation

1.Location Frequency (LF) 2.User Frequency (UF)

Example: Predict for Location E S.NLF S.UF LF.UF = LF x UFS.LF.UF NLF.UF = NLF x UFS.NLF.UF

Comparison & Evaluation PSMM: Periodic & Social Mobility Model SHM: Social-Historical Model CF: Collaborative Filtering gSCorr: Geo-Social Correlation

Contribution from Different Circles

Limitations Discrete Distant Diminishing Influence