people don't necessarily want to solve puzzles on their own. They often enjoy attacking them in online collaborative groups that include dozens, sometimes millions, of fans. These groups are collectively far smarter than their individual members, and regular puzzles don't stand a chance against that many brains.
Andreas Hotho's talk more specifically addressed the search for methods to identify tags which describe the same concept (or a more specific / a more general concept respectively) within a folksonomy. He suggested two approaches:
1. Applying measures directly to folksonomy statistics, allowing to describe tags as a vector; e.g. co-occurrence frequency and FolkRank could serve as a similarity measure (with these two having a tendency towards high-frequency tags) or a cosine method (which is more likely to produce "siblings")
2. Looking up tags in an external thesaurus/vocabulary (for instance achieving semantic grounding by mapping a tag and its most similar tags with Wordnet Synsets)
My topics of main interest are: 1) Associative Tags; 2) Agreement, Disagreement, discourse; 3) Corporate Semantic Web, 4) Are upper level ontologies/vocabularies not so bad after all?, 5) Cleaner schemas and ontologies