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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-07 17:32:43 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-07 17:32:43 +0000 |
commit | 6bf0a5cb5034a7e684dcc3500e841785237ce2dd (patch) | |
tree | a68f146d7fa01f0134297619fbe7e33db084e0aa /comm/mailnews/extensions/bayesian-spam-filter/nsBayesianFilter.h | |
parent | Initial commit. (diff) | |
download | thunderbird-6bf0a5cb5034a7e684dcc3500e841785237ce2dd.tar.xz thunderbird-6bf0a5cb5034a7e684dcc3500e841785237ce2dd.zip |
Adding upstream version 1:115.7.0.upstream/1%115.7.0upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to '')
-rw-r--r-- | comm/mailnews/extensions/bayesian-spam-filter/nsBayesianFilter.h | 397 |
1 files changed, 397 insertions, 0 deletions
diff --git a/comm/mailnews/extensions/bayesian-spam-filter/nsBayesianFilter.h b/comm/mailnews/extensions/bayesian-spam-filter/nsBayesianFilter.h new file mode 100644 index 0000000000..70d0a1a02b --- /dev/null +++ b/comm/mailnews/extensions/bayesian-spam-filter/nsBayesianFilter.h @@ -0,0 +1,397 @@ +/* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */ +/* This Source Code Form is subject to the terms of the Mozilla Public + * License, v. 2.0. If a copy of the MPL was not distributed with this + * file, You can obtain one at http://mozilla.org/MPL/2.0/. */ + +#ifndef nsBayesianFilter_h__ +#define nsBayesianFilter_h__ + +#include <stdio.h> +#include "nsCOMPtr.h" +#include "nsIMsgFilterPlugin.h" +#include "PLDHashTable.h" +#include "nsITimer.h" +#include "nsTArray.h" +#include "nsString.h" +#include "nsWeakReference.h" +#include "nsIObserver.h" +#include "nsHashPropertyBag.h" +#include "mozilla/intl/WordBreaker.h" + +#include "mozilla/ArenaAllocator.h" + +#define DEFAULT_MIN_INTERVAL_BETWEEN_WRITES 15 * 60 * 1000 + +struct Token; +class TokenEnumeration; +class TokenAnalyzer; +class nsIMsgWindow; +class nsIUTF8StringEnumerator; +struct BaseToken; +struct CorpusToken; + +/** + * Helper class to enumerate Token objects in a PLDHashTable + * safely and without copying (see bugzilla #174859). The + * enumeration is safe to use until an Add() + * or Remove() is performed on the table. + */ +class TokenEnumeration { + public: + explicit TokenEnumeration(PLDHashTable* table); + bool hasMoreTokens(); + BaseToken* nextToken(); + + private: + PLDHashTable::Iterator mIterator; +}; + +// A trait is some aspect of a message, like being junk or tagged as +// Personal, that the statistical classifier should track. The Trait +// structure is a per-token representation of information pertaining to +// a message trait. +// +// Traits per token are maintained as a linked list. +// +struct TraitPerToken { + uint32_t mId; // identifying number for a trait + uint32_t mCount; // count of messages with this token and trait + uint32_t mNextLink; // index in mTraitStore for the next trait, or 0 + // for none + TraitPerToken(uint32_t aId, uint32_t aCount); // inititializer +}; + +// An Analysis is the statistical results for a particular message, a +// particular token, and for a particular pair of trait/antitrait, that +// is then used in subsequent analysis to score the message. +// +// Analyses per token are maintained as a linked list. +// +struct AnalysisPerToken { + uint32_t mTraitIndex; // index representing a protrait/antitrait pair. + // So if we are analyzing 3 different traits, then + // the first trait is 0, the second 1, etc. + double mDistance; // absolute value of mProbability - 0.5 + double mProbability; // relative indicator of match of trait to token + uint32_t mNextLink; // index in mAnalysisStore for the Analysis object + // for the next trait index, or 0 for none. + // initializer + AnalysisPerToken(uint32_t aTraitIndex, double aDistance, double aProbability); +}; + +class TokenHash { + public: + virtual ~TokenHash(); + /** + * Clears out the previous message tokens. + */ + nsresult clearTokens(); + uint32_t countTokens(); + TokenEnumeration getTokens(); + BaseToken* add(const char* word); + + protected: + explicit TokenHash(uint32_t entrySize); + mozilla::ArenaAllocator<16384, 2> mWordPool; + uint32_t mEntrySize; + PLDHashTable mTokenTable; + char* copyWord(const char* word, uint32_t len); + BaseToken* get(const char* word); +}; + +class Tokenizer : public TokenHash { + public: + Tokenizer(); + ~Tokenizer(); + + Token* get(const char* word); + + // The training set keeps an occurrence count on each word. This count + // is supposed to count the # of messages it occurs in. + // When add/remove is called while tokenizing a message and NOT the training + // set, + // + Token* add(const char* word, uint32_t count = 1); + + Token* copyTokens(); + + void tokenize(const char* text); + + /** + * Creates specific tokens based on the mime headers for the message being + * tokenized + */ + void tokenizeHeaders(nsTArray<nsCString>& aHeaderNames, + nsTArray<nsCString>& aHeaderValues); + + void tokenizeAttachments(nsTArray<RefPtr<nsIPropertyBag2>>& attachments); + + nsCString mBodyDelimiters; // delimiters for body tokenization + nsCString mHeaderDelimiters; // delimiters for header tokenization + + // arrays of extra headers to tokenize / to not tokenize + nsTArray<nsCString> mEnabledHeaders; + nsTArray<nsCString> mDisabledHeaders; + // Delimiters used in tokenizing a particular header. + // Parallel array to mEnabledHeaders + nsTArray<nsCString> mEnabledHeadersDelimiters; + bool mCustomHeaderTokenization; // Are there any preference-set tokenization + // customizations? + uint32_t mMaxLengthForToken; // maximum length of a token + // should we convert iframe to div during tokenization? + bool mIframeToDiv; + + private: + void tokenize_ascii_word(char* word); + void tokenize_japanese_word(char* chunk); + inline void addTokenForHeader(const char* aTokenPrefix, nsACString& aValue, + bool aTokenizeValue = false, + const char* aDelimiters = nullptr); + nsresult stripHTML(const nsAString& inString, nsAString& outString); + // helper function to escape \n, \t, etc from a CString + void UnescapeCString(nsCString& aCString); + nsresult ScannerNext(const char16_t* text, int32_t length, int32_t pos, + bool isLastBuffer, int32_t* begin, int32_t* end, + bool* _retval); +}; + +/** + * Implements storage of a collection of message tokens and counts for + * a corpus of classified messages + */ + +class CorpusStore : public TokenHash { + public: + CorpusStore(); + ~CorpusStore(); + + /** + * retrieve the token structure for a particular string + * + * @param word the character representation of the token + * + * @return token structure containing counts, null if not found + */ + CorpusToken* get(const char* word); + + /** + * add tokens to the storage, or increment counts if already exists. + * + * @param aTokenizer tokenizer for the list of tokens to remember + * @param aTraitId id for the trait whose counts will be remembered + * @param aCount number of new messages represented by the token list + */ + void rememberTokens(Tokenizer& aTokenizer, uint32_t aTraitId, + uint32_t aCount); + + /** + * decrement counts for tokens in the storage, removing if all counts + * are zero + * + * @param aTokenizer tokenizer for the list of tokens to forget + * @param aTraitId id for the trait whose counts will be removed + * @param aCount number of messages represented by the token list + */ + void forgetTokens(Tokenizer& aTokenizer, uint32_t aTraitId, uint32_t aCount); + + /** + * write the corpus information to file storage + * + * @param aMaximumTokenCount prune tokens if number of tokens exceeds + * this value. == 0 for no pruning + */ + void writeTrainingData(uint32_t aMaximumTokenCount); + + /** + * read the corpus information from file storage + */ + void readTrainingData(); + + /** + * delete the local corpus storage file and data + */ + nsresult resetTrainingData(); + + /** + * get the count of messages whose tokens are stored that are associated + * with a trait + * + * @param aTraitId identifier for the trait + * @return number of messages for that trait + */ + uint32_t getMessageCount(uint32_t aTraitId); + + /** + * set the count of messages whose tokens are stored that are associated + * with a trait + * + * @param aTraitId identifier for the trait + * @param aCount number of messages for that trait + */ + void setMessageCount(uint32_t aTraitId, uint32_t aCount); + + /** + * get the count of messages associated with a particular token and trait + * + * @param token the token string and associated counts + * @param aTraitId identifier for the trait + */ + uint32_t getTraitCount(CorpusToken* token, uint32_t aTraitId); + + /** + * Add (or remove) data from a particular file to the corpus data. + * + * @param aFile the file with the data, in the format: + * + * Format of the trait file for version 1: + * [0xFCA93601] (the 01 is the version) + * for each trait to write: + * [id of trait to write] (0 means end of list) + * [number of messages per trait] + * for each token with non-zero count + * [count] + * [length of word]word + * + * @param aIsAdd should the data be added, or removed? true if adding, + * else removing. + * + * @param aFromTraits array of trait ids used in aFile. If aFile contains + * trait ids that are not in this array, they are not + * remapped, but assumed to be local trait ids. + * + * @param aToTraits array of trait ids, corresponding to elements of + * aFromTraits, that represent the local trait ids to be + * used in storing data from aFile into the local corpus. + * + */ + nsresult UpdateData(nsIFile* aFile, bool aIsAdd, + const nsTArray<uint32_t>& aFromTraits, + const nsTArray<uint32_t>& aToTraits); + + /** + * remove all counts (message and tokens) for a trait id + * + * @param aTrait trait id for the trait to remove + */ + nsresult ClearTrait(uint32_t aTrait); + + protected: + /** + * return the local corpus storage file for junk traits + */ + nsresult getTrainingFile(nsIFile** aFile); + + /** + * return the local corpus storage file for non-junk traits + */ + nsresult getTraitFile(nsIFile** aFile); + + /** + * read token strings from the data file + * + * @param stream file stream with token data + * @param fileSize file size + * @param aTraitId id for the trait whose counts will be read + * @param aIsAdd true to add the counts, false to remove them + * + * @return true if successful, false if error + */ + bool readTokens(FILE* stream, int64_t fileSize, uint32_t aTraitId, + bool aIsAdd); + + /** + * write token strings to the data file + */ + bool writeTokens(FILE* stream, bool shrink, uint32_t aTraitId); + + /** + * remove counts for a token string + */ + void remove(const char* word, uint32_t aTraitId, uint32_t aCount); + + /** + * add counts for a token string, adding the token string if new + */ + CorpusToken* add(const char* word, uint32_t aTraitId, uint32_t aCount); + + /** + * change counts in a trait in the traits array, adding the trait if needed + */ + nsresult updateTrait(CorpusToken* token, uint32_t aTraitId, + int32_t aCountChange); + nsCOMPtr<nsIFile> mTrainingFile; // file used to store junk training data + nsCOMPtr<nsIFile> mTraitFile; // file used to store non-junk + // training data + nsTArray<TraitPerToken> mTraitStore; // memory for linked-list of counts + uint32_t mNextTraitIndex; // index in mTraitStore to first empty + // TraitPerToken + nsTArray<uint32_t> mMessageCounts; // count of messages per trait + // represented in the store + nsTArray<uint32_t> mMessageCountsId; // Parallel array to mMessageCounts, + // with the corresponding trait ID +}; + +class nsBayesianFilter : public nsIJunkMailPlugin, + nsIMsgCorpus, + nsIObserver, + nsSupportsWeakReference { + public: + NS_DECL_ISUPPORTS + NS_DECL_NSIMSGFILTERPLUGIN + NS_DECL_NSIJUNKMAILPLUGIN + NS_DECL_NSIMSGCORPUS + NS_DECL_NSIOBSERVER + + nsBayesianFilter(); + + nsresult Init(); + + nsresult tokenizeMessage(const nsACString& messageURI, + nsIMsgWindow* aMsgWindow, TokenAnalyzer* analyzer); + void classifyMessage(Tokenizer& tokens, const nsACString& messageURI, + nsIJunkMailClassificationListener* listener); + + void classifyMessage(Tokenizer& tokenizer, const nsACString& messageURI, + nsTArray<uint32_t>& aProTraits, + nsTArray<uint32_t>& aAntiTraits, + nsIJunkMailClassificationListener* listener, + nsIMsgTraitClassificationListener* aTraitListener, + nsIMsgTraitDetailListener* aDetailListener); + + void observeMessage(Tokenizer& tokens, const nsACString& messageURI, + nsTArray<uint32_t>& oldClassifications, + nsTArray<uint32_t>& newClassifications, + nsIJunkMailClassificationListener* listener, + nsIMsgTraitClassificationListener* aTraitListener); + + protected: + virtual ~nsBayesianFilter(); + + static void TimerCallback(nsITimer* aTimer, void* aClosure); + + CorpusStore mCorpus; + double mJunkProbabilityThreshold; + int32_t mMaximumTokenCount; + bool mTrainingDataDirty; + int32_t mMinFlushInterval; // in milliseconds, must be positive + // and not too close to 0 + nsCOMPtr<nsITimer> mTimer; + + // index in mAnalysisStore for first empty AnalysisPerToken + uint32_t mNextAnalysisIndex; + // memory for linked list of AnalysisPerToken objects + nsTArray<AnalysisPerToken> mAnalysisStore; + /** + * Determine the location in mAnalysisStore where the AnalysisPerToken + * object for a particular token and trait is stored + */ + uint32_t getAnalysisIndex(Token& token, uint32_t aTraitIndex); + /** + * Set the value of the AnalysisPerToken object for a particular + * token and trait + */ + nsresult setAnalysis(Token& token, uint32_t aTraitIndex, double aDistance, + double aProbability); +}; + +#endif // _nsBayesianFilter_h__ |