示例#1
0
            private void TreeNodeChecked(object sender, RadTreeNodeEventArgs e)
            {
                RadTreeNode node   = e.Node;
                int         termId = int.Parse(node.Value);

                if (node.Checked)
                {
                    //Add Term
                    foreach (Term term in Terms)
                    {
                        if (term.TermId == termId)
                        {
                            SelectedTerms.Add(term);
                            break;
                        }
                    }
                }
                else
                {
                    //Remove Term
                    foreach (Term term in SelectedTerms)
                    {
                        if (term.TermId == termId)
                        {
                            SelectedTerms.Remove(term);
                            break;
                        }
                    }
                }

                //Rebind
                _tree.DataBind();
            }
        /// <summary>
        /// Scores the specified entry.
        /// </summary>
        /// <param name="entry">The entry.</param>
        /// <param name="context">The context.</param>
        /// <param name="log">The log.</param>
        /// <returns></returns>
        public override double Score(DocumentSelectResultEntry entry, DocumentSelectResult context, ILogBuilder log)
        {
            if (useMachineLearning)
            {
                WeightDictionary dc_vec = TermWeightModel.GetWeights(SelectedTerms.GetKeys(), entry.spaceDocument, context.spaceModel);

                var n_vec = fvConstructor.ConstructFeatureVector(dc_vec, entry.AssignedID);


                Double score = 0;
                Int32  l_id  = -1;
                if (sc_id.ContainsKey(entry.AssignedID))
                {
                    l_id = sc_id[entry.AssignedID];
                }

                score = classifier.DoScore(n_vec, log, l_id);

                return(score);
            }
            else
            {
                if (scoreDictionary.ContainsKey(entry.AssignedID))
                {
                    var fv = scoreDictionary[entry.AssignedID];
                    return(fv.CompressNumericVector(vectorCompression));
                }
                else
                {
                    return(0);
                }
            }
        }
        /// <summary>
        /// Computes score for given entry
        /// </summary>
        /// <param name="entry">The entry.</param>
        /// <param name="context">The context.</param>
        /// <param name="log">The log.</param>
        /// <returns></returns>
        public override double Score(DocumentSelectResultEntry entry, DocumentSelectResult context, ILogBuilder log)
        {
            Double output = 0;

            foreach (String term in entry.spaceDocument.terms.GetTokens())
            {
                Boolean isOk = true;
                if (context.selectedFeatures != null)
                {
                    if (context.selectedFeatures.Count > 0)
                    {
                        if (!context.selectedFeatures.ContainsKey(term))
                        {
                            isOk = false;
                        }
                    }
                }

                if (isOk && SelectedTerms != null)
                {
                    if (SelectedTerms.Count > 0)
                    {
                        if (!SelectedTerms.ContainsKey(term))
                        {
                            isOk = false;
                        }
                    }
                }

                if (isOk)
                {
                    if (queryTerms.Any())
                    {
                        if (queryTerms.Contains(term))
                        {
                            output += TermWeightModel.GetWeight(term, entry.spaceDocument, context.spaceModel);
                        }
                    }
                    else
                    {
                        output += TermWeightModel.GetWeight(term, entry.spaceDocument, context.spaceModel);
                    }
                }
            }



            return(output);
        }