1. API Guide
  2. Using the Data Mining API
  3. Data Mining With SQL
  4. Example : Building an ESA Model with a Wiki Dataset

27.5 Example : Building an ESA Model with a Wiki Dataset

The examples shows FEATURE_COMPARE function with Explicit Semantic Analysis (ESA) model, which compares a similar set of texts and then a dissimilar set of texts.

The example shows an ESA model built against a 2005 Wiki dataset rendering over 200,000 features. The documents are mined as text and the document titles are given as the feature IDs.

Similar Texts

SELECT 1-FEATURE_COMPARE(esa_wiki_mod USING 'There are several PGA tour golfers from South Africa' text AND USING 'Nick Price won the 2002 Mastercard Colonial Open' text) similarity FROM DUAL;

SIMILARITY
----------
      .258

The output metric shows distance calculation. Therefore, smaller number represent more similar texts. So, 1 minus the distance in the queries result in similarity.

Dissimilar Texts

SELECT 1-FEATURE_COMPARE(esa_wiki_mod USING 'There are several PGA tour golfers from South Africa' text AND USING 'John Elway played quarterback for the Denver Broncos' text) similarity FROM DUAL;

SIMILARITY
----------
      .007