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the record · 2005 · computational aesthetics

InterestMap: harvesting social network profiles for recommendations

Hugo Liu & Pattie Maes (2005). Proceedings of IUI Beyond Personalization 2005, San Diego, CA, 54–59.

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InterestMap tries to recommend for the whole person rather than for a single shopping session. It mined 100,000 public social-network profiles, segmented their free-form interest lists, normalized them against 21,000 interest and 1,000 identity descriptors, and learned a weighted network from co-occurrence. Spreading activation moved from a person's stated tastes through identity hubs and cultural cliques to candidate recommendations. In five-fold tests that hid half of each profile, the full network scored 0.86 on the paper's graded percentile measure; removing identity nodes reduced it to 0.81, and direct pairwise tallies scored 0.73. This was held-out profile reconstruction, not a user trial. The data also inherited duplicate accounts, heuristic normalization, public self-presentation, and the blind spots of a fixed ontology.

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