Create articleCountScoringStrategy

[paulalbert1]

Let's create a score that rewards articles in which there are few candidate articles retreived and penalizes cases in which a lot of articles are retrieved. This is consistent with Bayesian insights about probability.

To do this for each article, we need three values.

• countArticlesRetrieved - count of the articles retrieved; this is only for the articles actually retrieved; note that if we're using the strict name lookup strategy, you need not say, for example, that yiwang has 120,000 pubs
• articleCountThresholdScore - this is stored in application.properties
• articleCountWeight - this is also stored in application.properties

articleCountThresholdScore: 800
articleCountWeight: 200

1. Count the number of candidate articles retrieved. If retrieval was in strict mode, use the value from searchStrategy-leninent-threshold. Store as countArticlesRetrieved.

2. Retrieve articleCountThresholdScore and articleCountWeight from application.properties.

3. Set articleCount for each article equal to:

- (countArticlesRetrieved - articleCountThresholdScore) / articleCountWeight

4. Return following for each article:

countArticlesRetrieved: 380 /* sample value */
articleCountScore = 2.1 /* sample value */