private int compareByEnsemble(CSpellScore o1, CSpellScore o2)
{
int @out = 0;
OrthographicScore oScore1 = ((CSpellScore)o1).GetOScore();
OrthographicScore oScore2 = ((CSpellScore)o2).GetOScore();
FrequencyScore fScore1 = ((CSpellScore)o1).GetFScore();
FrequencyScore fScore2 = ((CSpellScore)o2).GetFScore();
ContextScore cScore1 = ((CSpellScore)o1).GetCScore();
ContextScore cScore2 = ((CSpellScore)o2).GetCScore();
double score1 = 0.6 * oScore1.GetScore() + 0.25 * fScore1.GetScore() + 0.15 * cScore1.GetScore();
double score2 = 0.6 * oScore2.GetScore() + 0.25 * fScore2.GetScore() + 0.15 * cScore2.GetScore();
// 1. compared by orthographic score, best
// SCR-2: use a fixed number to ensure result is not 0.
if (score2 > score1)
{
// from high to low
@out = 1;
}
else if (score2 < score1)
{
@out = -1;
}
// 2. alphabetic order
else
{
string cand1 = ((CSpellScore)o1).GetCandStr();
string cand2 = ((CSpellScore)o2).GetCandStr();
@out = cand2.CompareTo(cand1);
}
return(@out);
}
// check score rule for real-word merge correctionrrayList<TokenObj>
// nonSpaceTokenList,
private static bool IsTopCandValid(ContextScore orgContextScore, ContextScore topContextScore, double rwMergeFactor, bool debugFlag)
{
// Score rules for merge
double orgScore = orgContextScore.GetScore();
double topScore = topContextScore.GetScore();
bool flag = false;
// 2.1 no merge correction if orgScore is 0.0d, no word2Vec information
if (orgScore < 0.0d)
{
// 2.2a merge if the org score is negative and top score is positive
if (topScore > 0.0d)
{
flag = true;
}
// 2.2b merge if the org score is negative and top score is better
// this is needed for higher recall and F1
else if ((topScore < 0.0d) && (topScore > orgScore * rwMergeFactor))
{
flag = true;
}
}
else if (orgScore > 0.0d)
{
// 2.3a merge if the org score is positive and better 0.01*topScore
if (topScore * rwMergeFactor > orgScore)
{
flag = true;
}
}
return(flag);
}
private static void TestOnSet(Word2Vec w2vIm, Word2Vec w2vOm)
{
string inText = "He was diagnosed early on set dementia 3 years ago.";
TextObj textObj = new TextObj(inText);
List <TokenObj> inTextList = textObj.GetTokenList();
// remove space token from the list
List <TokenObj> nonSpaceTokenList = TextObj.GetNonSpaceTokenObjList(inTextList);
Console.WriteLine("==========================================");
Console.WriteLine("-- inTextList: [" + inText + "]");
int tarPos = 4;
int tarSize = 2; // "on set" has 2 tokens
int radius = 2;
bool word2VecSkipWord = true;
bool debugFlag = false;
// 1 context with window radius
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, w2vIm, radius, word2VecSkipWord, debugFlag);
string str1 = "onset";
ContextScore s1 = new ContextScore(str1, contextVec, w2vOm);
string str2 = "on set";
ContextScore s2 = new ContextScore(str2, contextVec, w2vOm);
Console.WriteLine("- [" + str1 + "]: " + s1.ToString());
Console.WriteLine("- [" + str2 + "]: " + s2.ToString());
}
// private methods
private static bool IsTopCandValidByScores(ContextScore orgContextScore, FrequencyScore orgFreqScore, ContextScore topContextScore, CSpellScore topCSpellScore, CSpellApi cSpellApi)
{
// init
bool flag = false;
double rw1To1CandCsFactor = cSpellApi.GetRankRw1To1CandCsFac();
double rw1To1WordMinCs = cSpellApi.GetRankRw1To1WordMinCs();
double rw1To1CandMinCs = cSpellApi.GetRankRw1To1CandMinCs();
double rw1To1CandCsDist = cSpellApi.GetRankRw1To1CandCsDist();
double rw1To1CandFsFactor = cSpellApi.GetRankRw1To1CandFsFac();
double rw1To1CandMinFs = cSpellApi.GetRankRw1To1CandMinFs();
double rw1To1CandFsDist = cSpellApi.GetRankRw1To1CandFsDist();
double orgScore = orgContextScore.GetScore();
double topScore = topContextScore.GetScore();
// another rule for word2Vec on real-word
// check contect score:
// 1. the topScore is bigger enough to cover the orgScore
// 2. the distance is > a value for confidence
if (((topScore / -orgScore) > rw1To1CandCsFactor) && (orgScore > rw1To1WordMinCs) && (topScore > rw1To1CandMinCs) && ((topScore - orgScore) > rw1To1CandCsDist)) //609|796|0.6920
// check frequency, all positive:
// 1. cand has better frequency
// 2. the difference is withint a range
{
double orgFScore = orgFreqScore.GetScore();
double topFScore = topCSpellScore.GetFScore().GetScore();
if (((topFScore / orgFScore) > rw1To1CandFsFactor) && (topFScore > rw1To1CandMinFs) && ((topFScore > orgFScore) || ((orgFScore - topFScore) < rw1To1CandFsDist))) // within freq range
{
flag = true;
}
}
return(flag);
}
/// <summary>
/// Compare two object o1 and o2. Both objects o1 and o2 are
/// FrequencyScore. The compare algorithm:
/// </summary>
/// <param name="o1"> first object to be compared </param>
/// <param name="o2"> second object to be compared
/// </param>
/// <returns> a negative integer, 0, or positive integer to represent the
/// object o1 is less, equals, or greater than object 02. </returns>
public virtual int Compare(ContextScore o1, ContextScore o2)
{
int @out = 0;
// 1. compare total score first
double score1 = ((ContextScore)o1).GetScore();
double score2 = ((ContextScore)o2).GetScore();
// SCR-2: use a fixed number to ensure result is not 0.
if (score2 > score1)
{
// from high to low
@out = 1;
}
else if (score2 < score1)
{
@out = -1;
}
else // 2. alphabetic order of word
{
string term1 = ((ContextScore)o1).GetTerm();
string term2 = ((ContextScore)o2).GetTerm();
@out = term2.CompareTo(term1);
}
return(@out);
}
// private constructor
public CSpellScore(string wordStr, string candStr, WordWcMap wordWcMap, DoubleVec contextVec, Word2Vec word2Vec, double wf1, double wf2, double wf3)
{
wordStr_ = wordStr;
candStr_ = candStr;
// calculate score
oScore_ = new OrthographicScore(wordStr_, candStr_, wf1, wf2, wf3);
fScore_ = new FrequencyScore(candStr_, wordWcMap);
nScore_ = new NoisyChannelScore(wordStr_, candStr_, wordWcMap, wf1, wf2, wf3);
cScore_ = new ContextScore(candStr_, contextVec, word2Vec);
}
// return the best ranked str from candidates using word2Vec score
// inTokenList, includes space token, is not coreTerm.Lc
// return null if no candidate is found to correct
public static MergeObj GetTopRankMergeObj(HashSet <MergeObj> candidates, List <TokenObj> nonSpaceTokenList, Word2Vec word2VecIm, Word2Vec word2VecOm, bool word2VecSkipWord, int contextRadius, double rwMergeFactor, bool debugFlag)
{
// init the topRankMergeObj
MergeObj topRankMergeObj = null;
if (candidates.Count > 0)
{
// 1. find sorted score list for each candidates ...
List <ContextScore> candScoreList = GetCandidateScoreList(candidates, nonSpaceTokenList, word2VecIm, word2VecOm, word2VecSkipWord, contextRadius, debugFlag);
// 2. find the top ranked str
// the 0 element has the highest score because it is sorted
// only 1 candidate, use it for nonWord
ContextScore topContextScore = null;
if (candScoreList.Count > 0)
{
topContextScore = candScoreList[0];
}
// 3. find the mergeObj from the topRankStr (if exist)
if (topContextScore != null)
{
// 3.1. convert mergeObj set to string set
// key: coreMergeWord, MergeObj
Dictionary <string, MergeObj> candStrMergeObjMap = new Dictionary <string, MergeObj>();
foreach (MergeObj mergeObj in candidates)
{
string mergeWord = mergeObj.GetCoreMergeWord();
candStrMergeObjMap[mergeWord] = mergeObj;
}
HashSet <string> andStrSet = new HashSet <string>(candStrMergeObjMap.Keys);
// 3.2 convert back from top rank str to MergeObj
// topRankStr should never be null because candidates is > 0
string topRankStr = topContextScore.GetTerm();
topRankMergeObj = candStrMergeObjMap.GetValueOrNull(topRankStr);
// 4. compare the top rank merge to the original string b4 merge
// 1. get the word2Vec score for the orgMergeTerm b4 merge
// 1.1 wordVec for context
int tarPos = topRankMergeObj.GetStartPos();
// tarSize is the total token No of the orgMergeWords
int tarSize = topRankMergeObj.GetEndPos() - topRankMergeObj.GetStartPos() + 1;
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, word2VecIm, contextRadius, word2VecSkipWord, debugFlag);
// 1.2 wordVec for the original words before merge
string orgMergeWord = topRankMergeObj.GetOrgMergeWord();
ContextScore orgContextScore = new ContextScore(orgMergeWord, contextVec, word2VecOm);
// validate top merge candidate, set to null if false
if (IsTopCandValid(orgContextScore, topContextScore, rwMergeFactor, debugFlag) == false)
{
// set to null if score is not good enough for corection
topRankMergeObj = null;
}
}
}
return(topRankMergeObj);
}
// private method
// Test merge and Split
private static void Test(string inText, int tarPos, int tarSize, int radius, string mergedWord, string splitWords, Word2Vec w2vIm, Word2Vec w2vOm)
{
// 0. process the inText
TextObj textObj = new TextObj(inText);
List <TokenObj> inTextList = textObj.GetTokenList();
// remove space token from the list
List <TokenObj> nonSpaceTokenList = TextObj.GetNonSpaceTokenObjList(inTextList);
Console.WriteLine("==========================================");
Console.WriteLine("-- inTextList: [" + inText + "]");
bool word2VecSkipWord = true;
bool debugFlag = false;
// 1.a context with window radius
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, w2vIm, radius, word2VecSkipWord, debugFlag);
// 1.b context with all inText
DoubleVec contextVecA = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, w2vIm, word2VecSkipWord, debugFlag);
// 1.c get score1
ContextScore score1 = new ContextScore(mergedWord, contextVec, w2vOm);
ContextScore score1a = new ContextScore(mergedWord, contextVecA, w2vOm);
Console.WriteLine(score1.ToString() + "|" + string.Format("{0,1:F8}", score1a.GetScore()));
// 2. split words
ContextScore score2 = new ContextScore(splitWords, contextVec, w2vOm);
ContextScore score2a = new ContextScore(splitWords, contextVecA, w2vOm);
Console.WriteLine(score2.ToString() + "|" + string.Format("{0,1:F8}", score2a.GetScore()));
// 3. 3. 3. Use avg. score on single words
// This method use different context for each single word
List <string> splitWordList = TermUtil.ToWordList(splitWords);
int index = 0;
double scoreSAvg = 0.0d; // radius
double scoreSAAvg = 0.0d; // all inText
//debugFlag = false;
foreach (string splitWord in splitWordList)
{
// window radius
DoubleVec contextVecS = Word2VecContext.GetContextVec(tarPos + index, 1, nonSpaceTokenList, w2vIm, radius, word2VecSkipWord, debugFlag);
ContextScore scoreS = new ContextScore(splitWord, contextVecS, w2vOm);
//System.out.println("-- " + scoreS.ToString());
scoreSAvg += scoreS.GetScore();
// all text
DoubleVec contextVecSA = Word2VecContext.GetContextVec(tarPos + index, 1, nonSpaceTokenList, w2vIm, word2VecSkipWord, debugFlag);
ContextScore scoreSA = new ContextScore(splitWord, contextVecSA, w2vOm);
//System.out.println("-- " + scoreSA.ToString());
scoreSAAvg += scoreSA.GetScore();
index++;
}
scoreSAvg = scoreSAvg / index; // window
scoreSAAvg = scoreSAAvg / index; // all text
Console.WriteLine("Avg. Single Word|" + string.Format("{0,1:F8}", scoreSAvg) + "|" + string.Format("{0,1:F8}", scoreSAAvg));
}
private static bool CheckRealWord1To1Rules(ContextScore topContextScore, string inStr, int tarPos, int tarSize, List <TokenObj> nonSpaceTokenList, Word2Vec word2VecIm, Word2Vec word2VecOm, bool word2VecSkipWord, int contextRadius, double rw1To1Factor, bool debugFlag)
{
// return false if no topCand found
if ((topContextScore == null) || (topContextScore.GetTerm().Equals(inStr)))
{
return(false);
}
// 1. get the word2Vec score for the org inStr b4 one-to-one
// 1.1 wordVec for context
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, word2VecIm, contextRadius, word2VecSkipWord, debugFlag);
// 1.2 wordVec for the original words before one-to-one
ContextScore orgCs = new ContextScore(inStr, contextVec, word2VecOm);
DebugPrint.Println("--- Real-Word One-To-One Context Score Detail: ---", debugFlag);
DebugPrint.Println("- Score - orgTerm: " + orgCs.ToString(), debugFlag);
DebugPrint.Println("- Score - top 1-to-1: " + topContextScore.ToString(), debugFlag);
DebugPrint.Println("- rw1To1Factor: " + rw1To1Factor, debugFlag);
// Score rules for one-to-one
double orgScore = orgCs.GetScore();
double topScore = topContextScore.GetScore();
bool flag = false;
// 2.1 no one-to-one correction if orgScore is 0.0d, no word2Vec information
if (orgScore < 0.0d)
{
// 2.2a one-to-one if the org score is negative and top score is positive
if (topScore > 0.0d)
{
// another rule for word2Vec on real-word
if (((topScore - orgScore) > 0.085) && (orgScore > -0.085)) // help from 0.6812 to 0.6877
{
flag = true;
}
}
// 2.2b one-to-one if the org score is negative and top score is better
else if ((topScore < 0.0d) && (topScore > orgScore * rw1To1Factor))
{
flag = true;
}
}
else if (orgScore > 0.0d)
{
// 2.3a merge if the org score is positive and better 0.01*topScore
if (topScore * rw1To1Factor > orgScore)
{
flag = true;
}
}
return(flag);
}
// return candidate set with context score
// word2Vec is the word|wordVec map to get the wordVec
// Not sorted, because it is a set
// tarPos: starting position of target token
// tarSize: token size of target token (single word = 1)
// contextRadius: windown radius
public static HashSet <ContextScore> GetCandidateScoreSet(HashSet <string> candidates, int tarPos, int tarSize, List <TokenObj> nonSpaceTokenList, Word2Vec word2VecIm, Word2Vec word2VecOm, bool word2VecSkipWord, int contextRadius, bool debugFlag)
{
// 1. get the context and contextVec, using input matrix
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, word2VecIm, contextRadius, word2VecSkipWord, debugFlag);
// 2. get context score for all candidates
HashSet <ContextScore> candScoreSet = new HashSet <ContextScore>();
foreach (string cand in candidates)
{
// get ContextSocre for each candidates, use output matrix
ContextScore cs = new ContextScore(cand, contextVec, word2VecOm);
candScoreSet.Add(cs);
}
return(candScoreSet);
}
// by combination, O, N, F, C
private int compareByCombo(CSpellScore o1, CSpellScore o2)
{
int @out = 0;
OrthographicScore oScore1 = ((CSpellScore)o1).GetOScore();
OrthographicScore oScore2 = ((CSpellScore)o2).GetOScore();
NoisyChannelScore nScore1 = ((CSpellScore)o1).GetNScore();
NoisyChannelScore nScore2 = ((CSpellScore)o2).GetNScore();
FrequencyScore fScore1 = ((CSpellScore)o1).GetFScore();
FrequencyScore fScore2 = ((CSpellScore)o2).GetFScore();
ContextScore cScore1 = ((CSpellScore)o1).GetCScore();
ContextScore cScore2 = ((CSpellScore)o2).GetCScore();
// 1. compared by orthographic score, best
if (oScore1.GetScore() != oScore2.GetScore())
{
OrthographicScoreComparator <OrthographicScore> osc = new OrthographicScoreComparator <OrthographicScore>();
@out = osc.Compare(oScore1, oScore2);
}
// 2. compared by noise channel score, 2nd best
else if (nScore1.GetScore() != nScore2.GetScore())
{
NoisyChannelScoreComparator <NoisyChannelScore> nsc = new NoisyChannelScoreComparator <NoisyChannelScore>();
@out = nsc.Compare(nScore1, nScore2);
}
// 3. compared by pure frequency score, 3rd best
else if (fScore1.GetScore() != fScore2.GetScore())
{
FrequencyScoreComparator <FrequencyScore> fsc = new FrequencyScoreComparator <FrequencyScore>();
@out = fsc.Compare(fScore1, fScore2);
}
// 4. compared by context score, 4 last
else if (cScore1.GetScore() != cScore2.GetScore())
{
ContextScoreComparator <ContextScore> csc = new ContextScoreComparator <ContextScore>();
@out = csc.Compare(cScore1, cScore2);
}
// 5. alphabetic order
else
{
string cand1 = ((CSpellScore)o1).GetCandStr();
string cand2 = ((CSpellScore)o2).GetCandStr();
@out = cand2.CompareTo(cand1);
}
return(@out);
}
// return candidate set with context score
// word2Vec is the word|wordVec map to get the wordVec
// Not sorted, because it is a set
// tarPos: starting position of target token
// tarSize: token size of target token (single word = 1)
public static HashSet <ContextScore> GetCandidateScoreSet(HashSet <MergeObj> candidates, List <TokenObj> nonSpaceTokenList, Word2Vec word2VecIm, Word2Vec word2VecOm, bool word2VecSkipWord, int contextRadius, bool debugFlag)
{
HashSet <ContextScore> candScoreSet = new HashSet <ContextScore>();
// get context score for all candidates
// go through all merge candidates, all have differetn context
foreach (MergeObj mergeObj in candidates)
{
// 1. get the context and contextVec, using input matrix
int tarPos = mergeObj.GetStartPos();
int tarSize = mergeObj.GetEndPos() - mergeObj.GetStartPos() + 1;
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, word2VecIm, contextRadius, word2VecSkipWord, debugFlag);
// 2. get ContextSocre for each merge, use output matrix
string mergeWord = mergeObj.GetCoreMergeWord();
ContextScore cs = new ContextScore(mergeWord, contextVec, word2VecOm);
candScoreSet.Add(cs);
}
return(candScoreSet);
}
// Use context and frequency scor eto validate the top ranked candidate
private static bool IsTopCandValid(string inStr, ContextScore orgContextScore, CSpellScore topCSpellScore, FrequencyScore orgFreqScore, CSpellApi cSpellApi, bool debugFlag)
{
ContextScore topContextScore = topCSpellScore.GetCScore();
// return false if no topCand found
if ((topContextScore == null) || (topContextScore.GetTerm().Equals(inStr)))
{
return(false);
}
// Score rules for one-to-one
double orgScore = orgContextScore.GetScore();
double topScore = topContextScore.GetScore();
bool flag = false;
double rw1To1CFactor = cSpellApi.GetRankRw1To1CFac();
// 2.1 no 1-to-1 correction if orgScore is 0.0d, no word2Vec information
if (orgScore < 0.0d)
{
// 2.2a one-to-one if the org score is negative and top score is positive
if (topScore > 0.0d)
{
// further check by ratio, dist, and min. by CScore and FScore
if (IsTopCandValidByScores(orgContextScore, orgFreqScore, topContextScore, topCSpellScore, cSpellApi) == true)
{
flag = true;
}
}
// 2.2b 1-to-1 if the org score is negative, top score is better
else if ((topScore < 0.0d) && (topScore > orgScore * rw1To1CFactor))
{
flag = true;
}
}
else if (orgScore > 0.0d)
{
// 2.3a merge if the org score is positive, better 0.01*topScore
if (topScore * rw1To1CFactor > orgScore)
{
flag = true;
}
}
return(flag);
}
// return the best ranked str from candidates using context score
// this method is replaced by GetTopRankStr, which sorted by comparator
public static string GetTopRankStrByScore(string inStr, HashSet <string> candidates, int tarPos, int tarSize, List <TokenObj> nonSpaceTokenList, Word2Vec word2VecIm, Word2Vec word2VecOm, bool word2VecSkipWord, int contextRadius, bool debugFlag)
{
// 1. get the context and contextVec
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, word2VecIm, contextRadius, word2VecSkipWord, debugFlag);
string topRankStr = inStr;
double maxScore = 0.0d;
foreach (string cand in candidates)
{
ContextScore cs = new ContextScore(cand, contextVec, word2VecOm);
double score = cs.GetScore();
// update only if the score is > 0.0d
if (score > maxScore)
{
topRankStr = cand;
maxScore = score;
}
}
return(topRankStr);
}
private int compareByContext(CSpellScore o1, CSpellScore o2)
{
int @out = 0;
ContextScore cScore1 = ((CSpellScore)o1).GetCScore();
ContextScore cScore2 = ((CSpellScore)o2).GetCScore();
// 1. compared by context score, 4 last
if (cScore1.GetScore() != cScore2.GetScore())
{
ContextScoreComparator <ContextScore> csc = new ContextScoreComparator <ContextScore>();
@out = csc.Compare(cScore1, cScore2);
}
// 2. alphabetic order
else
{
string cand1 = ((CSpellScore)o1).GetCandStr();
string cand2 = ((CSpellScore)o2).GetCandStr();
@out = cand2.CompareTo(cand1);
}
return(@out);
}
// return the best ranked str from candidates using word2Vec score
// inTokenList, includes space token, is not coreTerm.Lc
// return the orignal inStr if no candidate has score > 0.0d
public static string GetTopRankStr(string inStr, HashSet <string> candidates, int tarPos, int tarSize, List <TokenObj> nonSpaceTokenList, Word2Vec word2VecIm, Word2Vec word2VecOm, bool word2VecSkipWord, int contextRadius, int shortSplitWordLength, int maxShortSplitWordNo, double rwSplitFactor, int maxCandNo, bool debugFlag)
{
// init
string topRankStr = inStr;
// Find the correction str
if (candidates.Count > 0)
{
// 1. sorted score list for each candidates ...
// This ranking can be improved if n-gram model (frequecny) is used
List <ContextScore> candScoreList = RankByContext.GetCandidateScoreList(candidates, tarPos, tarSize, nonSpaceTokenList, word2VecIm, word2VecOm, word2VecSkipWord, contextRadius, debugFlag);
// 1.1 get the top tank candidate
ContextScore topContextScore = candScoreList[0];
// 2. validate the top rank
// 2.1 wordVec for context
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, word2VecIm, contextRadius, word2VecSkipWord, debugFlag);
// 2.2 wordVec for the original words before split
ContextScore orgContextScore = new ContextScore(inStr, contextVec, word2VecOm);
// 2.3 compare the top rank split to the original string b4 split
if (IsTopCandValid(inStr, orgContextScore, topContextScore, rwSplitFactor, debugFlag) == true)
{
// no correction: if score is not good enough for corection
topRankStr = topContextScore.GetTerm();
}
// debug print
if (debugFlag == true)
{
// print focus token (original)
DebugPrint.PrintCScore(orgContextScore.ToString(), debugFlag);
// print candidates
ContextScoreComparator <ContextScore> csc = new ContextScoreComparator <ContextScore>();
var list = candScoreList.OrderBy(x => x, csc).Take(maxCandNo).Select(obj => obj.ToString()).ToList();
foreach (var item in list)
{
DebugPrint.PrintCScore(item, debugFlag);
}
}
}
return(topRankStr);
}
// private methods
private static bool IsTopCandValid(string inStr, ContextScore orgContextScore, ContextScore topContextScore, double rwSplitFactor, bool debugFlag)
{
// return false if no topCand found
if ((topContextScore == null) || (topContextScore.GetTerm().Equals(inStr)))
{
return(false);
}
// Score rules for split
double orgScore = orgContextScore.GetScore();
double topScore = topContextScore.GetScore();
bool flag = false;
// 2.1 no split correction if orgScore is 0.0d, no word2Vec information
if (orgScore < 0.0d)
{
// 2.2a split if the org score is negative and top score is positive
if (topScore > 0.0d)
{
flag = true;
}
// 2.2b split if the org score is negative and top score is better
// not used for now, saved for future usage
else if ((topScore < 0.0d) && (topScore > orgScore * rwSplitFactor))
{
flag = true;
}
}
// not used for now, saved for future usage
else if (orgScore > 0.0d)
{
// 2.3a merge if the org score is positive and better 0.01*topScore
if (topScore * rwSplitFactor > orgScore)
{
flag = true;
}
}
return(flag);
}
// return the best ranked str from candidates using context score
// this method is replaced by GetTopRankStr, which sorted by comparator
public static MergeObj GetTopRankMergeObjByScore(HashSet <MergeObj> candidates, List <TokenObj> nonSpaceTokenList, Word2Vec word2VecIm, Word2Vec word2VecOm, bool word2VecSkipWord, int contextRadius, bool debugFlag)
{
MergeObj topRankMergeObj = null;
double maxScore = 0.0d;
foreach (MergeObj mergeObj in candidates)
{
// 1. get the context and contextVec
int tarPos = mergeObj.GetStartPos();
int tarSize = mergeObj.GetEndPos() - mergeObj.GetStartPos() + 1;
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, word2VecIm, contextRadius, word2VecSkipWord, debugFlag);
// 2. get ContextSocre for each merge, use output matrix
string mergeWord = mergeObj.GetCoreMergeWord();
ContextScore cs = new ContextScore(mergeWord, contextVec, word2VecOm);
double score = cs.GetScore();
// update only if the score is > 0.0d
if (score > maxScore)
{
topRankMergeObj = mergeObj;
maxScore = score;
}
}
return(topRankMergeObj);
}
// return the best ranked str from candidates using word2Vec score
// inTokenList, includes space token, is not coreTerm.Lc
// return the orignal inStr if no candidate has score > 0.0d
public static string GetTopRankStr(string inStr, HashSet <string> candidates, CSpellApi cSpellApi, int tarPos, List <TokenObj> nonSpaceTokenList, bool debugFlag)
{
// init
WordWcMap wordWcMap = cSpellApi.GetWordWcMap();
Word2Vec word2VecIm = cSpellApi.GetWord2VecIm();
Word2Vec word2VecOm = cSpellApi.GetWord2VecOm();
int contextRadius = cSpellApi.GetRw1To1ContextRadius();
bool word2VecSkipWord = cSpellApi.GetWord2VecSkipWord();
int maxCandNo = cSpellApi.GetCanMaxCandNo();
double wf1 = cSpellApi.GetOrthoScoreEdDistFac();
double wf2 = cSpellApi.GetOrthoScorePhoneticFac();
double wf3 = cSpellApi.GetOrthoScoreOverlapFac();
int tarSize = 1; // only for one-to-one, no merge here
string topRankStr = inStr;
// use cSpell top candidates
int topNo = 1; // top sort
string inStrLc = inStr.ToLower();
List <CSpellScore> cSpellScoreList = RankByCSpellRealWord1To1.GetCandidateScoreList(inStrLc, candidates, wordWcMap, tarPos, tarSize, nonSpaceTokenList, word2VecIm, word2VecOm, word2VecSkipWord, contextRadius, wf1, wf2, wf3, debugFlag);
// Find the correction str and correct
if (cSpellScoreList.Count > 0)
{
// the rw top rank must be in both NC and orthographic
CSpellScore topScore = cSpellScoreList[0];
double topFScore = topScore.GetFScore().GetScore(); //frequency
double topTScore = topScore.GetOScore().GetTokenScore(); // Token
double topPScore = topScore.GetOScore().GetPhoneticScore(); //Phone
double topOScore = topScore.GetOScore().GetOverlapScore(); //overlap
ContextScore orgContextScore = null;
// check the frequency
// get the max score of frequency, eidt, phonetic, and overlap
// the top rank must have all top score for above
if ((topFScore == CSpellScore.GetMaxFScore(cSpellScoreList)) && (topTScore == CSpellScore.GetMaxEScore(cSpellScoreList)) && (topPScore == CSpellScore.GetMaxPScore(cSpellScoreList)) && (topOScore == CSpellScore.GetMaxOScore(cSpellScoreList)))
{
ContextScore topContextScore = topScore.GetCScore();
// 1.1 wordVec for context
DoubleVec contextVec = Word2VecContext.GetContextVec(tarPos, tarSize, nonSpaceTokenList, word2VecIm, contextRadius, word2VecSkipWord, debugFlag);
// 1.2 wordVec for the original words before one-to-one
orgContextScore = new ContextScore(inStr, contextVec, word2VecOm);
FrequencyScore orgFScore = new FrequencyScore(inStr, wordWcMap);
// pass the orgContextScore
if (IsTopCandValid(inStr, orgContextScore, topScore, orgFScore, cSpellApi, debugFlag) == true)
{
// no correction: if score is not good enough for corection
topRankStr = topScore.GetCandStr();
// debug print for ananlysis
/// <summary>
///*
/// System.out.println("======= cSpellScoreList.size(): "
/// + cSpellScoreList.size() + " ========");
/// System.out.println(inStr
/// + "," + String.format("%1.8f", orgFScore.GetScore())
/// + "," + String.format("%1.8f", orgContextScore.GetScore()));
/// System.out.println(CSpellScore.GetScoreHeader());
/// for(CSpellScore cSpellScore: cSpellScoreList)
/// {
/// System.out.println(cSpellScore.ToString(","));
/// }
/// **
/// </summary>
}
}
// debug print
if (debugFlag == true)
{
// print focus token (original)
if (orgContextScore != null)
{
DebugPrint.PrintScore(orgContextScore.ToString(), debugFlag);
}
else
{
DebugPrint.PrintScore("No score for focus (" + inStr + ")", debugFlag);
}
// print candidate
var list = cSpellScoreList.Take(maxCandNo).Select(obj => obj.ToString()).ToList();
foreach (var item in list)
{
DebugPrint.PrintScore(item, debugFlag);
}
}
}
return(topRankStr);
}