diff --git a/README.md b/README.md index d951ef4..7c6b6a6 100644 --- a/README.md +++ b/README.md @@ -38,6 +38,7 @@ You need to train the model before it can rank documents. ```java package com.github.fairsearch.deltr; +import com.github.fairsearch.deltr.Deltr; import com.github.fairsearch.deltr.models.DeltrDoc; import com.github.fairsearch.deltr.models.DeltrDocImpl; import com.github.fairsearch.deltr.models.DeltrTopDocs; @@ -61,38 +62,38 @@ public class HelloWorld { // item 1 DeltrDoc item1 = new DeltrDocImpl(1, 1); // add the features to the document (featureName, featureValue, isProtected - since this is a protected feature) - item1.put("f0", 1.0, true); + item1.put("f0", true); // add the features to the document (featureName, featureValue) item1.put("f1", 0.962650646167003); // item 2 DeltrDoc item2 = new DeltrDocImpl(2, 0.98f); - item2.put("f0", 0.0, false); + item2.put("f0", false); item2.put("f1", 0.940172822166108); // item 3 DeltrDoc item3 = new DeltrDocImpl(3, 0.96f); - item3.put("f0", 0.0, false); + item3.put("f0", false); item3.put("f1", 0.925288002880488); // item 4 DeltrDoc item4 = new DeltrDocImpl(2, 0.94f); - item4.put("f0", 1.0, true); + item4.put("f0", true); item4.put("f1", 0.896143226020877); // item 5 DeltrDoc item5 = new DeltrDocImpl(3, 0.92f); - item5.put("f0", 0.0, false); + item5.put("f0", false); item5.put("f1", 0.89180775633204); // item 6 DeltrDoc item6 = new DeltrDocImpl(3, 0.9f); - item6.put("f0", 0.0, false); + item6.put("f0", false); item6.put("f1", 0.838704766545679); // add the items in the trainQuery DeltrDoc[] docsArr = new DeltrDoc[]{item1, item2, item3, item4, item5, item6}; - trainQuery.setDocs(docsArr); + trainQuery.put(docsArr); // the trainQuery to the trainSet trainSet.add(trainQuery); @@ -124,32 +125,32 @@ DeltrTopDocs preidictionSet = new DeltrTopDocsImpl(2); // 2 is the question ID // item 7 DeltrDoc item7 = new DeltrDocImpl(7, 0.9645f); // the current score is not really important -item7.put("f0", 0.0, false); +item7.put("f0", false); item7.put("f1", 0.9645); // item 8 DeltrDoc item8 = new DeltrDocImpl(8, 0.9524f); -item8.put("f0", 0.0, false); +item8.put("f0", false); item8.put("f1", 0.9524); // item 9 DeltrDoc item9 = new DeltrDocImpl(9, 0.9285f); -item9.put("f0", 0.0, false); +item9.put("f0", false); item9.put("f1", 0.9285); // item 10 DeltrDoc item10 = new DeltrDocImpl(10, 0.8961f); -item10.put("f0", 0.0, false); +item10.put("f0", false); item10.put("f1", 0.8961); // item 11 DeltrDoc item11 = new DeltrDocImpl(11, 0.8911f); -item11.put("f0", 1.0, true); +item11.put("f0", true); item11.put("f1", 0.8911); // item 12 DeltrDoc item12 = new DeltrDocImpl(12, 0.8312f); -item12.put("f0", 1.0, true); +item12.put("f0", true); item12.put("f1", 0.8312); //add the items in the set @@ -223,16 +224,18 @@ the tests, it can happen that (very rarely) they fail sometimes. The DELTR algorithm is described in this paper: -* Zehlike, Meike, and Carlos Castillo. "[Reducing Disparate Exposure in Ranking: -A Learning to Rank Approach](https://doi.org/10.1145/3132847.3132938)." arXiv preprint arXiv:1805.08716 (2018). +* Meike Zehlike, Gina-Theresa Diehn, Carlos Castillo. "[Reducing Disparate Exposure in Ranking: +A Learning to Rank Approach](https://arxiv.org/abs/1805.08716)." preprint arXiv:1805.08716 (2018). This library was developed by [Ivan Kitanovski](http://ivankitanovski.com/) based on the paper. See the -[license](https://github.com/fair-search/fairsearchdeltr-java/blob/master/LICENSE) file for more information. +[license](https://github.com/fair-search/fairsearch-deltr-java/blob/master/LICENSE) file for more information. + +For any questions contact [Meike Zehlike](https://de.linkedin.com/in/meike-zehlike-366bba131). ## See also -You can also see the [DELTR plug-in for ElasticSearch](https://github.com/fair-search/fairsearchdeltr-elasticsearch-plugin) - and [DELTR Python library](https://github.com/fair-search/fairsearchdeltr-python). +You can also see the [DELTR for ElasticSearch](https://github.com/fair-search/fairsearch-deltr-for-elasticsearch) + and [DELTR Python library](https://github.com/fair-search/fairsearch-deltr-python).