On finding common neighborhoods in massive graphs
Theoretical Computer Science
New results for finding common neighborhoods in massive graphs in the data stream model
Theoretical Computer Science
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The following notes summarize recent research into data-mining techniques that are in progress at Stanford: 1. The Google search engine: beating Yahoo et al. At their own game. 2. Query Flocks: Generalizing association rules/market baskets in a query precompiler that uses a relational DBMS effectively. 3. Synthesizing Knowledge from the Web: exploiting the Web's redundancy to extract data automatically. 4. Detecting Low-Frequency Events: Unlike marketing, where you only care about items that lots of people buy, extracting intelligence from text usually requires looking for a small number of unexpected juxtapositions of terms.