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yoffy |
1.1 |
unit GikoBayesian; |
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{! |
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\file GikoBayesian.pas |
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\brief ???ゃ?吾?≪?潟???c????/span> |
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yoffy |
1.6 |
$Id: GikoBayesian.pas,v 1.5 2004/10/21 03:46:57 yoffy Exp $ |
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yoffy |
1.1 |
} |
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interface |
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//================================================== |
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uses |
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//================================================== |
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yoffy |
1.4 |
Classes; |
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yoffy |
1.1 |
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//================================================== |
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type |
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//================================================== |
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{!*********************************************************** |
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\brief ??茯???????????/span> |
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************************************************************} |
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TWordInfo = class( TObject ) |
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private |
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FNormalWord : Integer; //!< ??絽吾????茯????????糸?眼????????/span> |
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FImportantWord : Integer; //!< 羈?????茯????????糸?眼????????/span> |
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FNormalText : Integer; //!< ??絽吾????茯??????????障??????????腴?????/span> |
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FImportantText : Integer; //!< 羈?????茯??????????障??????????腴?????/span> |
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public |
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property NormalWord : Integer read FNormalWord write FNormalWord; |
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property ImportantWord : Integer read FImportantWord write FImportantWord; |
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property NormalText : Integer read FNormalText write FNormalText; |
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property ImportantText : Integer read FImportantText write FImportantText; |
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end; |
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{!*********************************************************** |
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\brief 茹f??羝??水??茯???????????/span> |
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************************************************************} |
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TWordCountInfo = class( TObject ) |
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private |
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FWordCount : Integer; //!< ??茯???/span> |
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public |
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property WordCount : Integer read FWordCount write FWordCount; |
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end; |
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{!*********************************************************** |
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\brief 茹f??羝??水??茯????鴻?? |
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************************************************************} |
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// TWordCount = class( THashedStringList ) // 羶??? |
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yoffy |
1.3 |
TWordCount = class( TStringList ) |
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yoffy |
1.1 |
public |
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yoffy |
1.3 |
constructor Create; |
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yoffy |
1.1 |
destructor Destroy; override; |
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end; |
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{!*********************************************************** |
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\brief ???c???帥?≪???眼???冴?? |
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************************************************************} |
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TGikoBayesianAlgorithm = |
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(gbaPaulGraham, gbaGaryRonbinson{, gbaGaryRonbinsonFisher}); |
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{!*********************************************************** |
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\brief ???ゃ?吾?≪?潟???c????/span> |
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************************************************************} |
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yoffy |
1.3 |
// TGikoBayesian = class( THashedStringList ) // 羶??? |
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TGikoBayesian = class( TStringList ) |
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yoffy |
1.1 |
private |
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FFilePath : string; //!< 茯??粋昭???????<?ゃ??????/span> |
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function GetObject( const name : string ) : TWordInfo; |
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procedure SetObject( const name : string; value : TWordInfo ); |
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public |
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constructor Create; |
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destructor Destroy; override; |
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//! ???<?ゃ??????絖??絮ユ???茯??水?冴???障?? |
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procedure LoadFromFile( const filePath : string ); |
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//! ???<?ゃ?????膺?絮ユ???篆?絖????障?? |
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procedure SaveToFile( const filePath : string ); |
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//! ???<?ゃ?????膺?絮ユ???篆?絖????障?? |
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procedure Save; |
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//! ??茯???????????宴????緇????障?? |
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property Objects[ const name : string ] : TWordInfo |
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read GetObject write SetObject; default; |
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//! ??腴??????障??????茯????????潟?????障?? |
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procedure CountWord( |
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const text : string; |
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wordCount : TWordCount ); |
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{! |
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\brief Paul Graham 羈????冴?ャ??????腴???絵??墾??羆阪????障?? |
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\return ??腴???絵??墾 (羈??????ゃ?????? 0.0??1.0 羈??????鴻??) |
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} |
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function CalcPaulGraham( wordCount : TWordCount ) : Extended; |
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{! |
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\brief GaryRobinson 羈????冴?ャ??????腴???絵??墾??羆阪????障?? |
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\return ??腴???絵??墾 (羈??????ゃ?????? 0.0??1.0 羈??????鴻??) |
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} |
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function CalcGaryRobinson( wordCount : TWordCount ) : Extended; |
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// function CalcGaryRobinsonFisher( wordCount : TWordCount ) : Extended; |
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{! |
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\brief ??腴???茹f?? |
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\param text 茹f????????腴? |
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\param wordCount 茹f??????????茯????鴻????菴??? |
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\param algorithm 羈???墾??浦絎??????????≪???眼???冴??????絎????障?? |
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\return ??腴???絵??墾 (羈??????ゃ?????? 0.0??1.0 羈??????鴻??) |
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CountWord ? Calcxxxxx ???障???????茵??????????с???? |
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} |
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function Parse( |
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const text : string; |
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wordCount : TWordCount; |
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algorithm : TGikoBayesianAlgorithm = gbaGaryRonbinson |
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) : Extended; |
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{! |
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\brief 絖?????? |
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\param wordCount Parse ?цВ??????????茯????鴻?? |
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\param isImportant 羈??????鴻????腴???????????????? True |
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} |
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procedure Learn( |
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wordCount : TWordCount; |
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isImportant : Boolean ); |
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{! |
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\brief 絖??腟?????綽????? |
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\param wordCount Parse ?цВ??????????茯????鴻?? |
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\param isImportant 羈??????鴻????腴???????????????????????? True |
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\warning 絖??羝??帥????腴???????????∈茯??堺?ャ?障??????<br> |
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Learn ????????????腴??? isImportant ???????c????????腴??? |
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Forget ?????????若?帥???若?鴻???贋?????障????<br> |
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絖??羝??帥???????????????????????????????? |
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???????膺?腟??????????≪????????с???????障??????<br> |
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wordCount ??緇?????腴? (Parse ? text 綣??? ???膺?腟??????帥?????≪???障????<br><br> |
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筝祉??絵????腴?????羈?????腴????????帥????????? Forget -> Learn ?????т戎?????障???? |
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} |
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procedure Forget( |
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wordCount : TWordCount; |
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isImportant : Boolean ); |
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end; |
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//================================================== |
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implementation |
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//================================================== |
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uses |
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yoffy |
1.4 |
SysUtils, Math, Windows; |
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yoffy |
1.1 |
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const |
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GIKO_BAYESIAN_FILE_VERSION = '1.0'; |
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yoffy |
1.3 |
{ |
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Modes = (ModeWhite, ModeGraph, ModeAlpha, ModeHanKana, ModeNum, |
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ModeWGraph, ModeWAlpha, ModeWNum, |
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ModeWHira, ModeWKata, ModeWKanji); |
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} |
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CharMode1 : array [ 0..255 ] of Byte = |
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( |
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
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0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, |
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2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, |
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1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, |
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3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, |
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1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, |
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3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 0, |
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
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0, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, |
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4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, |
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4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, |
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yoffy |
1.6 |
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, |
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yoffy |
1.3 |
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, |
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
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); |
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yoffy |
1.1 |
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//************************************************************ |
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// misc |
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//************************************************************ |
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//============================== |
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// RemoveToken |
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//============================== |
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function RemoveToken(var s: string;const delimiter: string): string; |
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var |
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p: Integer; |
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begin |
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p := AnsiPos(delimiter, s); |
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if p = 0 then |
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Result := s |
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else |
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Result := Copy(s, 1, p - 1); |
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s := Copy(s, Length(Result) + Length(delimiter) + 1, Length(s)); |
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end; |
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//============================== |
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// AbsSort |
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//============================== |
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function AbsSort( p1, p2 : Pointer ) : Integer; |
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var |
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v1, v2 : Single; |
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begin |
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v1 := Abs( Single( p1 ) - 0.5 ); |
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v2 := Abs( Single( p2 ) - 0.5 ); |
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if v1 > v2 then |
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Result := -1 |
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else if v1 = v2 then |
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Result := 0 |
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else |
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Result := 1; |
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end; |
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//************************************************************ |
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// TWordCount class |
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//************************************************************ |
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yoffy |
1.3 |
constructor TWordCount.Create; |
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begin |
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Duplicates := dupIgnore; |
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CaseSensitive := True; |
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Sorted := True; |
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end; |
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yoffy |
1.1 |
destructor TWordCount.Destroy; |
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var |
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i : Integer; |
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begin |
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for i := Count - 1 downto 0 do |
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if Objects[ i ] <> nil then |
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Objects[ i ].Free; |
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inherited; |
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end; |
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//************************************************************ |
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// TGikoBayesian class |
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//************************************************************ |
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//============================== |
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// Create |
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//============================== |
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constructor TGikoBayesian.Create; |
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begin |
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yoffy |
1.3 |
Duplicates := dupIgnore; |
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CaseSensitive := True; |
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Sorted := True; |
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yoffy |
1.1 |
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end; |
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//============================== |
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// Destroy |
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//============================== |
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destructor TGikoBayesian.Destroy; |
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var |
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i : Integer; |
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begin |
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for i := Count - 1 downto 0 do |
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if inherited Objects[ i ] <> nil then |
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inherited Objects[ i ].Free; |
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inherited; |
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end; |
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procedure TGikoBayesian.LoadFromFile( const filePath : string ); |
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var |
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i : Integer; |
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sl : TStringList; |
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s : string; |
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name : string; |
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info : TWordInfo; |
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begin |
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yoffy |
1.2 |
FFilePath := filePath; |
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yoffy |
1.1 |
if not FileExists( filePath ) then |
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Exit; |
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yoffy |
1.2 |
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yoffy |
1.1 |
sl := TStringList.Create; |
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try |
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sl.LoadFromFile( filePath ); |
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for i := 1 to sl.Count - 1 do begin |
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s := sl[ i ]; |
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name := RemoveToken( s, #1 ); |
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info := TWordInfo.Create; |
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info.NormalWord := StrToIntDef( '$' + RemoveToken( s, #1 ), 0 ); |
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info.ImportantWord := StrToIntDef( '$' + RemoveToken( s, #1 ), 0 ); |
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info.NormalText := StrToIntDef( '$' + RemoveToken( s, #1 ), 0 ); |
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info.ImportantText := StrToIntDef( '$' + RemoveToken( s, #1 ), 0 ); |
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AddObject( name, info ); |
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end; |
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finally |
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sl.Free; |
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end; |
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end; |
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procedure TGikoBayesian.SaveToFile( const filePath : string ); |
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var |
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i : Integer; |
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sl : TStringList; |
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s : string; |
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info : TWordInfo; |
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begin |
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yoffy |
1.2 |
FFilePath := filePath; |
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yoffy |
1.1 |
sl := TStringList.Create; |
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try |
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sl.BeginUpdate; |
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sl.Add( GIKO_BAYESIAN_FILE_VERSION ); |
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for i := 0 to Count - 1 do begin |
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info := TWordInfo( inherited Objects[ i ] ); |
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s := Strings[ i ] + #1 |
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+ Format('%x', [info.NormalWord]) + #1 |
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+ Format('%x', [info.ImportantWord]) + #1 |
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+ Format('%x', [info.NormalText]) + #1 |
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+ Format('%x', [info.ImportantText]); |
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sl.Add(s); |
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end; |
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sl.EndUpdate; |
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sl.SaveToFile( filePath ); |
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finally |
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sl.Free; |
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end; |
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end; |
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procedure TGikoBayesian.Save; |
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begin |
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if FFilePath <> '' then |
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SaveToFile( FFilePath ); |
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end; |
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//============================== |
| 361 |
|
|
// GetObject |
| 362 |
|
|
//============================== |
| 363 |
|
|
function TGikoBayesian.GetObject( const name : string ) : TWordInfo; |
| 364 |
|
|
var |
| 365 |
|
|
idx : Integer; |
| 366 |
|
|
begin |
| 367 |
|
|
|
| 368 |
yoffy |
1.3 |
idx := IndexOf( name ); // 羶??? |
| 369 |
yoffy |
1.1 |
if idx < 0 then |
| 370 |
|
|
Result := nil |
| 371 |
|
|
else |
| 372 |
|
|
Result := TWordInfo( inherited Objects[ idx ] ); |
| 373 |
|
|
|
| 374 |
|
|
end; |
| 375 |
|
|
|
| 376 |
|
|
//============================== |
| 377 |
|
|
// SetObject |
| 378 |
|
|
//============================== |
| 379 |
|
|
procedure TGikoBayesian.SetObject( const name : string; value : TWordInfo ); |
| 380 |
|
|
var |
| 381 |
|
|
idx : Integer; |
| 382 |
|
|
begin |
| 383 |
|
|
|
| 384 |
|
|
idx := IndexOf( name ); |
| 385 |
|
|
if idx < 0 then |
| 386 |
|
|
AddObject( name, value ) |
| 387 |
|
|
else |
| 388 |
|
|
inherited Objects[ idx ] := value; |
| 389 |
|
|
|
| 390 |
|
|
end; |
| 391 |
|
|
|
| 392 |
|
|
|
| 393 |
|
|
//============================== |
| 394 |
|
|
// CountWord |
| 395 |
|
|
//============================== |
| 396 |
|
|
procedure TGikoBayesian.CountWord( |
| 397 |
|
|
const text : string; |
| 398 |
|
|
wordCount : TWordCount ); |
| 399 |
|
|
type |
| 400 |
yoffy |
1.3 |
Modes = (ModeWhite, ModeGraph, ModeAlpha, ModeHanKana, ModeNum, |
| 401 |
yoffy |
1.1 |
ModeWGraph, ModeWAlpha, ModeWNum, |
| 402 |
|
|
ModeWHira, ModeWKata, ModeWKanji); |
| 403 |
|
|
var |
| 404 |
|
|
p, tail, last : PChar; |
| 405 |
|
|
mode, newMode : Modes; |
| 406 |
|
|
aWord : string; |
| 407 |
|
|
ch : Longword; |
| 408 |
|
|
chSize : Integer; |
| 409 |
|
|
delimiter : TStringList; |
| 410 |
|
|
delimited : Boolean; |
| 411 |
|
|
i, idx : Integer; |
| 412 |
|
|
countInfo : TWordCountInfo; |
| 413 |
|
|
const |
| 414 |
|
|
KAKUJOSI = '??' + #10 + '??#39; + #10 + '??' + #10 + '??#39; + #10 + '????' + |
| 415 |
|
|
#10 + '??#39; + #10 + '??#39; + #10 + '????' + #10 + '?障??#39;; |
| 416 |
yoffy |
1.5 |
kKanji = [$80..$A0, $E0..$ff]; |
| 417 |
yoffy |
1.1 |
begin |
| 418 |
|
|
|
| 419 |
|
|
delimiter := TStringList.Create; |
| 420 |
|
|
try |
| 421 |
|
|
mode := ModeWhite; |
| 422 |
|
|
delimiter.Text := KAKUJOSI; |
| 423 |
|
|
p := PChar( text ); |
| 424 |
|
|
tail := p + Length( text ); |
| 425 |
|
|
last := p; |
| 426 |
|
|
|
| 427 |
|
|
while p < tail do begin |
| 428 |
|
|
delimited := False; |
| 429 |
|
|
// ??絖????帥?ゃ?????ゅ??/span> |
| 430 |
|
|
// ?糸???鴻? ModeGraph ?????????у???ャ???綽?????????????? |
| 431 |
yoffy |
1.5 |
// if Byte(Byte( p^ ) - $a1) < $5e then begin |
| 432 |
|
|
if Byte( p^ ) in kKanji then begin |
| 433 |
yoffy |
1.1 |
if p + 1 < tail then begin |
| 434 |
|
|
ch := (PByte( p )^ shl 8) or PByte( p + 1 )^; |
| 435 |
|
|
case ch of |
| 436 |
|
|
$8140: newMode := ModeWhite; |
| 437 |
|
|
$8141..$824e: newMode := ModeWGraph; |
| 438 |
|
|
$824f..$8258: newMode := ModeWNum; |
| 439 |
|
|
$8260..$829a: newMode := ModeWAlpha; |
| 440 |
|
|
$829f..$82f1: newMode := ModeWHira; |
| 441 |
|
|
$8340..$8396: newMode := ModeWKata; |
| 442 |
|
|
else newMode := ModeWKanji; |
| 443 |
|
|
end; |
| 444 |
yoffy |
1.6 |
// '??????#39; ??抗篁??????障???????帥?????????障???? |
| 445 |
|
|
if (mode = ModeWHira) or (mode = ModeWKata) then |
| 446 |
|
|
if ch in [$814a, $814b, $815b] then |
| 447 |
|
|
newMode := mode; |
| 448 |
yoffy |
1.1 |
end else begin |
| 449 |
|
|
newMode := ModeWhite; |
| 450 |
|
|
end; |
| 451 |
|
|
|
| 452 |
|
|
chSize := 2; |
| 453 |
|
|
|
| 454 |
|
|
// ?阪????????????絖?????????罎??祉???? |
| 455 |
|
|
if p + 3 < tail then begin // 3 = delimiter ????紊у?? - 1 |
| 456 |
|
|
for i := 0 to delimiter.Count - 1 do begin |
| 457 |
|
|
if CompareMem( |
| 458 |
|
|
p, PChar( delimiter[ i ] ), Length( delimiter[ i ] ) ) then begin |
| 459 |
|
|
delimited := True; |
| 460 |
|
|
chSize := Length( delimiter[ i ] ); |
| 461 |
|
|
Break; |
| 462 |
|
|
end; |
| 463 |
|
|
end; |
| 464 |
|
|
end; |
| 465 |
|
|
end else begin |
| 466 |
yoffy |
1.3 |
newMode := Modes( CharMode1[ Byte( p^ ) ] ); |
| 467 |
yoffy |
1.1 |
|
| 468 |
|
|
chSize := 1; |
| 469 |
|
|
end; |
| 470 |
|
|
|
| 471 |
|
|
if (mode <> newMode) or delimited then begin |
| 472 |
|
|
|
| 473 |
|
|
// ??絖????帥?ゃ????紊??眼?????? |
| 474 |
|
|
// ????????阪????????????絖??????????? |
| 475 |
|
|
if mode <> ModeWhite then begin |
| 476 |
yoffy |
1.3 |
SetLength( aWord, p - last ); |
| 477 |
|
|
CopyMemory( PChar( aWord ), last, p - last ); |
| 478 |
yoffy |
1.5 |
//aWord := Copy( last, 0, p - last ); |
| 479 |
yoffy |
1.3 |
idx := wordCount.IndexOf( aWord ); // ?? |
| 480 |
yoffy |
1.1 |
if idx < 0 then begin |
| 481 |
|
|
countInfo := TWordCountInfo.Create; |
| 482 |
|
|
wordCount.AddObject( aWord, countInfo ); |
| 483 |
|
|
end else begin |
| 484 |
|
|
countInfo := TWordCountInfo( wordCount.Objects[ idx ] ); |
| 485 |
|
|
end; |
| 486 |
|
|
countInfo.WordCount := countInfo.WordCount + 1; |
| 487 |
|
|
end; |
| 488 |
|
|
|
| 489 |
|
|
last := p; |
| 490 |
|
|
mode := newMode; |
| 491 |
|
|
|
| 492 |
|
|
end; |
| 493 |
|
|
|
| 494 |
|
|
p := p + chSize; |
| 495 |
|
|
end; // while |
| 496 |
|
|
|
| 497 |
|
|
if mode <> ModeWhite then begin |
| 498 |
|
|
aWord := Copy( last, 0, p - last ); |
| 499 |
|
|
idx := wordCount.IndexOf( aWord ); |
| 500 |
|
|
if idx < 0 then begin |
| 501 |
|
|
countInfo := TWordCountInfo.Create; |
| 502 |
|
|
wordCount.AddObject( aWord, countInfo ); |
| 503 |
|
|
end else begin |
| 504 |
|
|
countInfo := TWordCountInfo( wordCount.Objects[ idx ] ); |
| 505 |
|
|
end; |
| 506 |
|
|
countInfo.WordCount := countInfo.WordCount + 1; |
| 507 |
|
|
end; |
| 508 |
|
|
finally |
| 509 |
|
|
delimiter.Free; |
| 510 |
|
|
end; |
| 511 |
|
|
|
| 512 |
|
|
end; |
| 513 |
|
|
|
| 514 |
|
|
//============================== |
| 515 |
|
|
// CalcPaulGraham |
| 516 |
|
|
//============================== |
| 517 |
|
|
function TGikoBayesian.CalcPaulGraham( wordCount : TWordCount ) : Extended; |
| 518 |
|
|
|
| 519 |
|
|
function p( const aWord : string ) : Single; |
| 520 |
|
|
var |
| 521 |
|
|
info : TWordInfo; |
| 522 |
|
|
begin |
| 523 |
|
|
info := Objects[ aWord ]; |
| 524 |
|
|
if info = nil then |
| 525 |
|
|
Result := 0.4 |
| 526 |
|
|
else if info.NormalWord = 0 then |
| 527 |
|
|
Result := 0.99 |
| 528 |
|
|
else if info.ImportantWord = 0 then |
| 529 |
|
|
Result := 0.01 |
| 530 |
|
|
else |
| 531 |
|
|
Result := ( info.ImportantWord / info.ImportantText ) / |
| 532 |
|
|
((info.NormalWord * 2 / info.NormalText ) + |
| 533 |
|
|
(info.ImportantWord / info.ImportantText)); |
| 534 |
|
|
end; |
| 535 |
|
|
|
| 536 |
|
|
var |
| 537 |
|
|
s, q : Extended; |
| 538 |
|
|
i : Integer; |
| 539 |
|
|
narray : TList; |
| 540 |
|
|
const |
| 541 |
|
|
SAMPLE_COUNT = 15; |
| 542 |
|
|
begin |
| 543 |
|
|
|
| 544 |
|
|
Result := 1; |
| 545 |
|
|
if wordCount.Count = 0 then |
| 546 |
|
|
Exit; |
| 547 |
|
|
|
| 548 |
|
|
narray := TList.Create; |
| 549 |
|
|
try |
| 550 |
|
|
for i := 0 to wordCount.Count - 1 do begin |
| 551 |
|
|
narray.Add( Pointer( p( wordCount[ i ] ) ) ); |
| 552 |
|
|
end; |
| 553 |
|
|
|
| 554 |
|
|
narray.Sort( AbsSort ); |
| 555 |
|
|
|
| 556 |
|
|
s := 1; |
| 557 |
|
|
q := 1; |
| 558 |
|
|
i := min( SAMPLE_COUNT, narray.Count ); |
| 559 |
|
|
while i > 0 do begin |
| 560 |
|
|
Dec( i ); |
| 561 |
|
|
s := s * Single( narray[ i ] ); |
| 562 |
|
|
q := q * (1 - Single( narray[ i ] )); |
| 563 |
|
|
end; |
| 564 |
|
|
|
| 565 |
|
|
Result := s / (s + q); |
| 566 |
|
|
finally |
| 567 |
|
|
narray.Free; |
| 568 |
|
|
end; |
| 569 |
|
|
|
| 570 |
|
|
end; |
| 571 |
|
|
|
| 572 |
|
|
//============================== |
| 573 |
|
|
// CalcGaryRobinson |
| 574 |
|
|
//============================== |
| 575 |
|
|
function TGikoBayesian.CalcGaryRobinson( wordCount : TWordCount ) : Extended; |
| 576 |
|
|
|
| 577 |
|
|
function p( const aWord : string ) : Single; |
| 578 |
|
|
var |
| 579 |
|
|
info : TWordInfo; |
| 580 |
|
|
begin |
| 581 |
|
|
info := Objects[ aWord ]; |
| 582 |
|
|
if info = nil then |
| 583 |
|
|
Result := 0.415 |
| 584 |
|
|
else if info.ImportantWord = 0 then |
| 585 |
|
|
Result := 0.0001 |
| 586 |
|
|
else if info.NormalWord = 0 then |
| 587 |
|
|
Result := 0.9999 |
| 588 |
|
|
else |
| 589 |
|
|
Result := ( info.ImportantWord / info.ImportantText ) / |
| 590 |
|
|
((info.NormalWord / info.NormalText ) + |
| 591 |
|
|
(info.ImportantWord / info.ImportantText)); |
| 592 |
|
|
end; |
| 593 |
|
|
|
| 594 |
|
|
function f( cnt : Integer; n, mean : Single ) : Extended; |
| 595 |
|
|
const |
| 596 |
|
|
k = 0.00001; |
| 597 |
|
|
begin |
| 598 |
|
|
Result := ( (k * mean) + (cnt * n) ) / (k + cnt); |
| 599 |
|
|
end; |
| 600 |
|
|
|
| 601 |
|
|
var |
| 602 |
|
|
n : Extended; |
| 603 |
|
|
narray : array of Single; |
| 604 |
|
|
mean : Extended; |
| 605 |
|
|
countInfo : TWordCountInfo; |
| 606 |
|
|
i : Integer; |
| 607 |
|
|
normal : Extended; |
| 608 |
|
|
important : Extended; |
| 609 |
|
|
cnt : Extended; |
| 610 |
|
|
begin |
| 611 |
|
|
|
| 612 |
|
|
if wordCount.Count = 0 then begin |
| 613 |
|
|
Result := 1; |
| 614 |
|
|
Exit; |
| 615 |
|
|
end; |
| 616 |
|
|
|
| 617 |
|
|
SetLength( narray, wordCount.Count ); |
| 618 |
|
|
mean := 0; |
| 619 |
|
|
for i := 0 to wordCount.Count - 1 do begin |
| 620 |
|
|
n := p( wordCount[ i ] ); |
| 621 |
|
|
narray[ i ] := n; |
| 622 |
|
|
mean := mean + n; |
| 623 |
|
|
end; |
| 624 |
|
|
mean := mean / wordCount.Count; |
| 625 |
|
|
|
| 626 |
|
|
cnt := 0; |
| 627 |
|
|
normal := 1; |
| 628 |
|
|
important := 1; |
| 629 |
|
|
for i := 0 to wordCount.Count - 1 do begin |
| 630 |
|
|
countInfo := TWordCountInfo( wordCount.Objects[ i ] ); |
| 631 |
|
|
n := f( countInfo.WordCount, narray[ i ], mean ); |
| 632 |
|
|
normal := normal * n; |
| 633 |
|
|
important := important * (1 - n); |
| 634 |
|
|
if countInfo <> nil then |
| 635 |
|
|
cnt := cnt + countInfo.WordCount; |
| 636 |
|
|
end; |
| 637 |
|
|
if cnt = 0 then |
| 638 |
|
|
cnt := 1; |
| 639 |
|
|
normal := 1 - Exp( Ln( normal ) * (1 / cnt) ); |
| 640 |
|
|
important := 1 - Exp( Ln( important ) * (1 / cnt) ); |
| 641 |
|
|
|
| 642 |
|
|
n := (important - normal+ 0.00001) / (important + normal + 0.00001); |
| 643 |
|
|
Result := (1 + n) / 2; |
| 644 |
|
|
|
| 645 |
|
|
end; |
| 646 |
|
|
|
| 647 |
|
|
//============================== |
| 648 |
|
|
// Parse |
| 649 |
|
|
//============================== |
| 650 |
|
|
function TGikoBayesian.Parse( |
| 651 |
|
|
const text : string; |
| 652 |
|
|
wordCount : TWordCount; |
| 653 |
|
|
algorithm : TGikoBayesianAlgorithm = gbaGaryRonbinson |
| 654 |
|
|
) : Extended; |
| 655 |
|
|
begin |
| 656 |
|
|
|
| 657 |
|
|
CountWord( text, wordCount ); |
| 658 |
|
|
case algorithm of |
| 659 |
|
|
gbaPaulGraham: Result := CalcPaulGraham( wordCount ); |
| 660 |
|
|
gbaGaryRonbinson: Result := CalcGaryRobinson( wordCount ); |
| 661 |
|
|
else Result := 0; |
| 662 |
|
|
end; |
| 663 |
|
|
|
| 664 |
|
|
end; |
| 665 |
|
|
|
| 666 |
|
|
//============================== |
| 667 |
|
|
// Learn |
| 668 |
|
|
//============================== |
| 669 |
|
|
procedure TGikoBayesian.Learn( |
| 670 |
|
|
wordCount : TWordCount; |
| 671 |
|
|
isImportant : Boolean ); |
| 672 |
|
|
var |
| 673 |
|
|
aWord : string; |
| 674 |
|
|
wordinfo : TWordInfo; |
| 675 |
|
|
countinfo : TWordCountInfo; |
| 676 |
yoffy |
1.3 |
i : Integer; |
| 677 |
yoffy |
1.1 |
begin |
| 678 |
|
|
|
| 679 |
|
|
for i := 0 to wordCount.Count - 1 do begin |
| 680 |
|
|
aWord := wordCount[ i ]; |
| 681 |
|
|
wordinfo := Objects[ aWord ]; |
| 682 |
yoffy |
1.3 |
countinfo := TWordCountInfo( wordCount.Objects[ i ] ); |
| 683 |
yoffy |
1.1 |
if wordinfo = nil then begin |
| 684 |
|
|
wordinfo := TWordInfo.Create; |
| 685 |
|
|
Objects[ aWord ] := wordinfo; |
| 686 |
|
|
end; |
| 687 |
|
|
|
| 688 |
|
|
if isImportant then begin |
| 689 |
|
|
wordinfo.ImportantWord := wordinfo.ImportantWord + countinfo.WordCount; |
| 690 |
|
|
wordinfo.ImportantText := wordinfo.ImportantText + 1; |
| 691 |
|
|
end else begin |
| 692 |
|
|
wordinfo.NormalWord := wordinfo.NormalWord + countinfo.WordCount; |
| 693 |
|
|
wordinfo.NormalText := wordinfo.NormalText + 1; |
| 694 |
|
|
end; |
| 695 |
|
|
end; |
| 696 |
|
|
|
| 697 |
|
|
end; |
| 698 |
|
|
|
| 699 |
|
|
//============================== |
| 700 |
|
|
// Forget |
| 701 |
|
|
//============================== |
| 702 |
|
|
procedure TGikoBayesian.Forget( |
| 703 |
|
|
wordCount : TWordCount; |
| 704 |
|
|
isImportant : Boolean ); |
| 705 |
|
|
var |
| 706 |
|
|
aWord : string; |
| 707 |
|
|
wordinfo : TWordInfo; |
| 708 |
|
|
countinfo : TWordCountInfo; |
| 709 |
|
|
i : Integer; |
| 710 |
|
|
begin |
| 711 |
|
|
|
| 712 |
|
|
for i := 0 to wordCount.Count - 1 do begin |
| 713 |
|
|
aWord := wordCount[ i ]; |
| 714 |
|
|
wordinfo := Objects[ aWord ]; |
| 715 |
|
|
if wordinfo = nil then |
| 716 |
|
|
Continue; |
| 717 |
|
|
|
| 718 |
|
|
countinfo := TWordCountInfo( wordCount.Objects[ i ] ); |
| 719 |
|
|
if isImportant then begin |
| 720 |
|
|
wordinfo.ImportantWord := wordinfo.ImportantWord - countinfo.WordCount; |
| 721 |
|
|
wordinfo.ImportantText := wordinfo.ImportantText - 1; |
| 722 |
|
|
end else begin |
| 723 |
|
|
wordinfo.NormalWord := wordinfo.NormalWord - countinfo.WordCount; |
| 724 |
|
|
wordinfo.NormalText := wordinfo.NormalText - 1; |
| 725 |
|
|
end; |
| 726 |
|
|
end; |
| 727 |
|
|
|
| 728 |
|
|
end; |
| 729 |
|
|
|
| 730 |
|
|
end. |