Esempio n. 1
0
        public void Store(string filepath)
        {
            StreamWriter fs     = new StreamWriter(filepath, false);
            string       csvStr = "";

            Int64 avg = count / corpus.Count + 2;

            int csvC = 0;

            foreach (var entry in corpus)
            {
                nGramDist ngd = entry.Value;

                if (ngd.isSalient && ngd.total > avg)
                {
                    csvStr  = "'" + entry.Key + "',";
                    csvStr += ngd.negCnt + ",";
                    csvStr += ngd.posCnt + ",";
                    csvStr += ngd.nutCnt + ",";
                    csvStr += ngd.bias + ",";
                    csvStr += ngd.objective + ",";
                    csvStr += ngd.total;
                    csvC++;
                    fs.WriteLine(csvStr);
                }
            }
            Console.WriteLine(csvC);
            fs.Close();
        }
Esempio n. 2
0
        public double score(string line)
        {
            double score = 0.0;

            line = line.ToLower();
            line = line.Replace(",", "");
            line = line.Replace(".", "");
            line = line.Replace("!", "");
            line = line.Replace("?", "");
            line = line.Replace("\"", "");
            line = line.Replace("'", "");
            line = line.Replace("#", "");

            string[] ngrams = NGramify(line);

            double negS = 0.0000001, posS = 0.0000001, objS = 0.0000001;

            foreach (string ng in ngrams)
            {
                if (corpus.ContainsKey(ng))
                {
                    nGramDist ngd = corpus[ng];

                    //if (ngd.isSalient)
                    {
                        if (ngd.objective > 0.5)
                        {
                            objS += ngd.objective;
                        }
                        else
                        {
                            double bias = ngd.bias;

                            if (bias < 0)
                            {
                                negS -= bias;
                            }
                            else
                            {
                                posS += bias;
                            }
                        }
                    }
                }
            }

            if (objS > negS && objS > posS)
            {
                return(0);
            }

            if (negS > posS)
            {
                return(-negS / (negS + posS + objS));
            }
            else if (negS < posS)
            {
                return(posS / (negS + posS + objS));
            }

            score = (posS - negS) / (negS + posS + objS);
            return(score);
        }