This is very simple search implementation for the cranfield dataset.
Cranfield is a small curated dataset that is very extensively used in the information retrieval experiments. In the dataset, there are 226 queries (search terms), 1400 documents, and 1837 (evaluations). The dataset is supposed to be complete in the sense that the documents that should be returned for each known are known. This makes the evaluation easier. Click here more details
Yes!. Try to run the class edu.kennesaw.cs.core.EvalSearch in Java or the file eval.py in Python. The expected output looks like as below:
Final ncdg for all queries is {} 0.6301330740878168
nDCG is a very common metric used in search evaluations. Higher nDCG score (close to 1.0 ) describes a search system that gives all the relevant results with most relevant ones on the top.
Try to modify the code such that you can increase the nDCG score.