A system and related techniques permit a search service operator to access a variety of disparate relevance measures, and integrate those measures into idealized or unified data sets. A search service operator may employ self-learning networks to generate relevance rankings of Web site hits in response to user queries or searches, such as Boolean text or other searches. To improve the accuracy and quality of the rankings of results, the service provider may accept as inputs relevance measures created from query logs, from human-annotated search records, from independent commercial or other search sites, or from other sources and feed those measures to a normalization engine. That engine may normalize those relevance ratings to a common scale, such as quintiles, percentages or other scales or levels. The provider may then use that idealized or normalized combined measure to, for example, train the search algorithms or heuristics to arrive at better or more accurate results.