Esempio n. 1
0
File: CG.cs Progetto: wxbjs/Allcea
        public AbsoluteEffectivenessEstimate Estimate(Run run, IRelevanceEstimator relEstimator, IConfidenceEstimator confEstimator)
        {
            double e = 0, var = 0;

            // Traverse docs retrieved
            foreach (string doc in run.Documents) {
                RelevanceEstimate docEst = relEstimator.Estimate(run.Query, doc);
                e += docEst.Expectation;
                var += docEst.Variance;
            }
            // Compute average
            e /= run.Documents.Count();
            var /= run.Documents.Count() * run.Documents.Count();
            // Normalize between 0 and 1
            e /= this.MaxRelevance;
            var /= this.MaxRelevance * this.MaxRelevance;

            Estimate est = new Estimate(e, var);

            return new AbsoluteEffectivenessEstimate(run.System, run.Query,
                e, var,
                confEstimator.EstimateInterval(est), confEstimator.EstimateAbsoluteConfidence(est));
        }
Esempio n. 2
0
File: CG.cs Progetto: wxbjs/Allcea
        public RelativeEffectivenessEstimate Estimate(Run runA, Run runB, IRelevanceEstimator relEstimator, IConfidenceEstimator confEstimator)
        {
            double e = 0, var = 0;

            // Traverse docs retrieved by A
            HashSet<string> inRunA = new HashSet<string>(); // retrieved by run A
            foreach (string doc in runA.Documents) {
                RelevanceEstimate docEst = relEstimator.Estimate(runA.Query, doc);
                e += docEst.Expectation;
                var += docEst.Variance;
                inRunA.Add(doc);
            }
            // Traverse docs retrieved by B
            foreach (string doc in runB.Documents) {
                RelevanceEstimate docEst = relEstimator.Estimate(runB.Query, doc);
                e -= docEst.Expectation;
                if (inRunA.Contains(doc)) {
                    // If retrieved in both runs, does not contribute to variance
                    var -= docEst.Variance;
                } else {
                    var += docEst.Variance;
                }
            }
            // Compute average
            e /= inRunA.Count;
            var /= inRunA.Count * inRunA.Count;
            // Normalize between 0 and 1
            e /= this.MaxRelevance;
            var /= this.MaxRelevance * this.MaxRelevance;

            Estimate est = new Estimate(e, var);

            return new RelativeEffectivenessEstimate(runA.System, runB.System, runA.Query,
                e, var,
                confEstimator.EstimateInterval(est), confEstimator.EstimateRelativeConfidence(est));
        }