+++ /dev/null
-function bayesTrain(id, train_up, event) {
- try {
-
- event.stopPropagation();
-
- var query = "backend.php?op=pluginhandler&plugin=af_sort_bayes&method=trainArticle&article_id=" + param_escape(id) +
- "&train_up=" + param_escape(train_up);
-
- notify_progress("Loading, please wait...");
-
- new Ajax.Request("backend.php", {
- parameters: query,
- onComplete: function(transport) {
- notify(transport.responseText);
- updateScore(id);
- } });
-
- } catch (e) {
- exception_error("showTrgmRelated", e);
- }
-}
-
-function bayesClearDatabase() {
- try {
-
- if (confirm(__("Clear classifier database?"))) {
-
- var query = "backend.php?op=pluginhandler&plugin=af_sort_bayes&method=clearDatabase";
-
- new Ajax.Request("backend.php", {
- parameters: query,
- onComplete: function (transport) {
- notify(transport.responseText);
- bayesUpdateUI();
- }
- });
- }
-
- } catch (e) {
- exception_error("showTrgmRelated", e);
- }
-}
-
-function bayesUpdateUI() {
- try {
-
- var query = "backend.php?op=pluginhandler&plugin=af_sort_bayes&method=renderPrefsUI";
-
- new Ajax.Request("backend.php", {
- parameters: query,
- onComplete: function (transport) {
- dijit.byId("af_sort_bayes_prefs").attr("content", transport.responseText);
- }
- });
-
- } catch (e) {
- exception_error("showTrgmRelated", e);
- }
-}
-
-function bayesShow(id) {
- try {
- if (dijit.byId("bayesShowDlg"))
- dijit.byId("bayesShowDlg").destroyRecursive();
-
- var query = "backend.php?op=pluginhandler&plugin=af_sort_bayes&method=showArticleStats&article_id=" + param_escape(id);
-
- dialog = new dijit.Dialog({
- id: "bayesShowDlg",
- title: __("Classifier information"),
- style: "width: 600px",
- href: query});
-
- dialog.show();
-
- } catch (e) {
- exception_error("shareArticle", e);
- }
-}
-
-
+++ /dev/null
-<?php
-
-class Af_Sort_Bayes extends Plugin {
-
- private $host;
- private $filters = array();
- private $dbh;
- private $score_modifier = 50;
- private $sql_prefix = "ttrss_plugin_af_sort_bayes";
- private $auto_categorize_threshold = 10000;
- private $max_document_length = 3000; // classifier can't rescale output for very long strings apparently
-
- function about() {
- return array(1.0,
- "Bayesian classifier for tt-rss (WIP)",
- "fox");
- }
-
- function init($host) {
- require_once __DIR__ . "/lib/class.naivebayesian.php";
- //require_once __DIR__ . "/lib/class.naivebayesian_ngram.php";
- require_once __DIR__ . "/lib/class.naivebayesianstorage.php";
-
- $this->host = $host;
- $this->dbh = Db::get();
-
- $this->init_database();
-
- $host->add_hook($host::HOOK_ARTICLE_FILTER, $this);
- $host->add_hook($host::HOOK_PREFS_TAB, $this);
- $host->add_hook($host::HOOK_ARTICLE_BUTTON, $this);
-
- }
-
- function trainArticle() {
- $article_id = (int) $_REQUEST["article_id"];
- $train_up = sql_bool_to_bool($_REQUEST["train_up"]);
-
- //$category = $train_up ? "GOOD" : "UGLY";
- $dst_category = "UGLY";
-
- $nbs = new NaiveBayesianStorage($_SESSION["uid"]);
- $nb = new NaiveBayesian($nbs);
-
- $result = $this->dbh->query("SELECT score, guid, title, content FROM ttrss_entries, ttrss_user_entries WHERE ref_id = id AND id = " .
- $article_id . " AND owner_uid = " . $_SESSION["uid"]);
-
- if ($this->dbh->num_rows($result) != 0) {
- $guid = $this->dbh->fetch_result($result, 0, "guid");
- $title = $this->dbh->fetch_result($result, 0, "title");
- $content = mb_substr(mb_strtolower($title . " " . strip_tags($this->dbh->fetch_result($result, 0, "content"))), 0, $this->max_document_length);
- $score = $this->dbh->fetch_result($result, 0, "score");
-
- $this->dbh->query("BEGIN");
-
- $ref = $nbs->getReference($guid, false);
-
- if (isset($ref['category_id'])) {
- $current_category = $nbs->getCategoryById($ref['category_id']);
- } else {
- $current_category = "UGLY";
- }
-
- // set score to fixed value for now
-
- if ($train_up) {
- switch ($current_category) {
- case "UGLY":
- $dst_category = "GOOD";
- $score = $this->score_modifier;
- break;
- case "BAD":
- $dst_category = "UGLY";
- $score = 0;
- break;
- case "GOOD":
- $dst_category = "GOOD";
- break;
- }
- } else {
- switch ($current_category) {
- case "UGLY":
- $dst_category = "BAD";
- $score = -$this->score_modifier;
- break;
- case "BAD":
- $dst_category = "BAD";
- break;
- case "GOOD":
- $dst_category = "UGLY";
- $score = 0;
- break;
- }
- }
-
- $nb->untrain($guid, $content);
- $nb->train($guid, $nbs->getCategoryByName($dst_category), $content);
-
- $this->dbh->query("UPDATE ttrss_user_entries SET score = '$score' WHERE ref_id = $article_id AND owner_uid = " . $_SESSION["uid"]);
-
- $nb->updateProbabilities();
-
- $this->dbh->query("COMMIT");
-
- }
-
- print "$article_id :: $dst_category :: $score";
- }
-
- function get_js() {
- return file_get_contents(__DIR__ . "/init.js");
- }
-
- function get_prefs_js() {
- return file_get_contents(__DIR__ . "/init.js");
- }
-
- function hook_article_button($line) {
- return "<img src=\"plugins/af_sort_bayes/thumb_up.png\"
- style=\"cursor : pointer\" style=\"cursor : pointer\"
- onclick=\"bayesTrain(".$line["id"].", true, event)\"
- class='tagsPic' title='".__('+1')."'>" .
- "<img src=\"plugins/af_sort_bayes/thumb_down.png\"
- style=\"cursor : pointer\" style=\"cursor : pointer\"
- onclick=\"bayesTrain(".$line["id"].", false, event)\"
- class='tagsPic' title='".__('-1')."'>" .
- "<img src=\"plugins/af_sort_bayes/chart_bar.png\"
- style=\"cursor : pointer\" style=\"cursor : pointer\"
- onclick=\"bayesShow(".$line["id"].")\"
- class='tagsPic' title='".__('Show classifier info')."'>";
-
- }
-
- function init_database() {
- $prefix = $this->sql_prefix;
-
- // TODO there probably should be a way for plugins to determine their schema version to upgrade tables
-
- /*$this->dbh->query("DROP TABLE IF EXISTS ${prefix}_wordfreqs", false);
- $this->dbh->query("DROP TABLE IF EXISTS ${prefix}_references", false);
- $this->dbh->query("DROP TABLE IF EXISTS ${prefix}_categories", false);*/
-
- $this->dbh->query("BEGIN");
-
- // PG only for the time being
-
- if (DB_TYPE == "mysql") {
-
- $this->dbh->query("CREATE TABLE IF NOT EXISTS ${prefix}_categories (
- id INTEGER NOT NULL PRIMARY KEY auto_increment,
- category varchar(100) NOT NULL DEFAULT '',
- probability DOUBLE NOT NULL DEFAULT '0',
- owner_uid INTEGER NOT NULL,
- FOREIGN KEY (owner_uid) REFERENCES ttrss_users(id) ON DELETE CASCADE,
- word_count BIGINT NOT NULL DEFAULT '0') ENGINE=InnoDB");
-
- $this->dbh->query("CREATE TABLE IF NOT EXISTS ${prefix}_references (
- id INTEGER NOT NULL PRIMARY KEY auto_increment,
- document_id VARCHAR(255) NOT NULL,
- category_id INTEGER NOT NULL,
- FOREIGN KEY (category_id) REFERENCES ${prefix}_categories(id) ON DELETE CASCADE,
- owner_uid INTEGER NOT NULL,
- FOREIGN KEY (owner_uid) REFERENCES ttrss_users(id) ON DELETE CASCADE) ENGINE=InnoDB");
-
- $this->dbh->query("CREATE TABLE IF NOT EXISTS ${prefix}_wordfreqs (
- word varchar(100) NOT NULL DEFAULT '',
- category_id INTEGER NOT NULL,
- FOREIGN KEY (category_id) REFERENCES ${prefix}_categories(id) ON DELETE CASCADE,
- owner_uid INTEGER NOT NULL,
- FOREIGN KEY (owner_uid) REFERENCES ttrss_users(id) ON DELETE CASCADE,
- count BIGINT NOT NULL DEFAULT '0') ENGINE=InnoDB");
-
-
- } else {
- $this->dbh->query("CREATE TABLE IF NOT EXISTS ${prefix}_categories (
- id SERIAL NOT NULL PRIMARY KEY,
- category varchar(100) NOT NULL DEFAULT '',
- probability DOUBLE PRECISION NOT NULL DEFAULT '0',
- owner_uid INTEGER NOT NULL REFERENCES ttrss_users(id) ON DELETE CASCADE,
- word_count BIGINT NOT NULL DEFAULT '0')");
-
- $this->dbh->query("CREATE TABLE IF NOT EXISTS ${prefix}_references (
- id SERIAL NOT NULL PRIMARY KEY,
- document_id VARCHAR(255) NOT NULL,
- category_id INTEGER NOT NULL REFERENCES ${prefix}_categories(id) ON DELETE CASCADE,
- owner_uid INTEGER NOT NULL REFERENCES ttrss_users(id) ON DELETE CASCADE)");
-
- $this->dbh->query("CREATE TABLE IF NOT EXISTS ${prefix}_wordfreqs (
- word varchar(100) NOT NULL DEFAULT '',
- category_id INTEGER NOT NULL REFERENCES ${prefix}_categories(id) ON DELETE CASCADE,
- owner_uid INTEGER NOT NULL REFERENCES ttrss_users(id) ON DELETE CASCADE,
- count BIGINT NOT NULL DEFAULT '0')");
- }
-
- $owner_uid = @$_SESSION["uid"];
-
- if ($owner_uid) {
- $result = $this->dbh->query("SELECT id FROM ${prefix}_categories WHERE owner_uid = $owner_uid LIMIT 1");
-
- if ($this->dbh->num_rows($result) == 0) {
- $this->dbh->query("INSERT INTO ${prefix}_categories (category, owner_uid) VALUES ('GOOD', $owner_uid)");
- $this->dbh->query("INSERT INTO ${prefix}_categories (category, owner_uid) VALUES ('BAD', $owner_uid)");
- $this->dbh->query("INSERT INTO ${prefix}_categories (category, owner_uid) VALUES ('UGLY', $owner_uid)");
- }
- }
-
- $this->dbh->query("COMMIT");
- }
-
- function renderPrefsUI() {
- $result = $this->dbh->query("SELECT category, probability, word_count,
- (SELECT COUNT(id) FROM {$this->sql_prefix}_references WHERE
- category_id = {$this->sql_prefix}_categories.id) as doc_count
- FROM {$this->sql_prefix}_categories WHERE owner_uid = " . $_SESSION["uid"]);
-
- print "<h3>" . __("Statistics") . "</h3>";
-
- print "<p>".T_sprintf("Required UGLY word count for automatic matching: %d", $this->auto_categorize_threshold)."</p>";
-
- print "<table>";
- print "<tr><th>Category</th><th>Probability</th><th>Words</th><th>Articles</th></tr>";
-
- while ($line = $this->dbh->fetch_assoc($result)) {
- print "<tr>";
- foreach ($line as $k => $v) {
- if ($k == "probability") $v = sprintf("%.3f", $v);
-
- print "<td>$v</td>";
- }
- print "</tr>";
- }
-
- print "</table>";
-
- print "<h3>" . __("Last matched articles") . "</h3>";
-
- $result = $this->dbh->query("SELECT te.title, category, tf.title AS feed_title
- FROM ttrss_entries AS te, ttrss_user_entries AS tu, ttrss_feeds AS tf, {$this->sql_prefix}_references AS tr, {$this->sql_prefix}_categories AS tc
- WHERE tf.id = tu.feed_id AND tu.ref_id = te.id AND tc.id = tr.category_id AND tr.document_id = te.guid ORDER BY te.id DESC LIMIT 20");
-
- print "<ul class=\"browseFeedList\" style=\"border-width : 1px\">";
-
- while ($line = $this->dbh->fetch_assoc($result)) {
- print "<li>" . $line["category"] . ": " . $line["title"] . " (" . $line["feed_title"] . ")</li>";
- }
-
- print "</ul>";
-
- print "<button dojoType=\"dijit.form.Button\" onclick=\"return bayesUpdateUI()\">".
- __('Refresh')."</button> ";
-
- print "<button dojoType=\"dijit.form.Button\" onclick=\"return bayesClearDatabase()\">".
- __('Clear database')."</button> ";
-
- //
- }
-
- function hook_prefs_tab($args) {
- if ($args != "prefPrefs") return;
-
- print "<div id=\"af_sort_bayes_prefs\" dojoType=\"dijit.layout.AccordionPane\" title=\"".__('Bayesian classifier (af_sort_bayes)')."\">";
-
- $this->renderPrefsUI();
-
- print "</div>";
- }
-
- function hook_article_filter($article) {
- $owner_uid = $article["owner_uid"];
-
- // guid already includes owner_uid so we don't need to include it
- $result = $this->dbh->query("SELECT id FROM {$this->sql_prefix}_references WHERE
- document_id = '" . $this->dbh->escape_string($article['guid_hashed']) . "'");
-
- if (db_num_rows($result) != 0) {
- _debug("bayes: article already categorized");
- return $article;
- }
-
- $nbs = new NaiveBayesianStorage($owner_uid);
- $nb = new NaiveBayesian($nbs);
-
- $categories = $nbs->getCategories();
-
- if (count($categories) > 0) {
-
- $count_neutral = 0;
-
- $id_good = 0;
- $id_ugly = 0;
- $id_bad = 0;
-
- foreach ($categories as $id => $cat) {
- if ($cat["category"] == "GOOD") {
- $id_good = $id;
- } else if ($cat["category"] == "UGLY") {
- $id_ugly = $id;
- $count_neutral += $cat["word_count"];
- } else if ($cat["category"] == "BAD") {
- $id_bad = $id;
- }
- }
-
- $dst_category = $id_ugly;
-
- $bayes_content = mb_substr(mb_strtolower($article["title"] . " " . strip_tags($article["content"])), 0, $this->max_document_length);
-
- if ($count_neutral >= $this->auto_categorize_threshold) {
- // enable automatic categorization
-
- $result = $nb->categorize($bayes_content);
-
- //print_r($result);
-
- if (count($result) == 3) {
- $prob_good = $result[$id_good];
- $prob_bad = $result[$id_bad];
-
- if (!is_nan($prob_good) && $prob_good > 0.90) {
- $dst_category = $id_good;
- $article["score_modifier"] += $this->score_modifier;
- } else if (!is_nan($prob_bad) && $prob_bad > 0.90) {
- $dst_category = $id_bad;
- $article["score_modifier"] -= $this->score_modifier;
- }
- }
-
- _debug("bayes, dst category: $dst_category");
- }
-
- $nb->train($article["guid_hashed"], $dst_category, $bayes_content);
-
- $nb->updateProbabilities();
- }
-
- return $article;
-
- }
-
- function clearDatabase() {
- $prefix = $this->sql_prefix;
-
- $this->dbh->query("BEGIN");
- $this->dbh->query("DELETE FROM ${prefix}_references WHERE owner_uid = " . $_SESSION["uid"]);
- $this->dbh->query("DELETE FROM ${prefix}_wordfreqs WHERE owner_uid = " . $_SESSION["uid"]);
- $this->dbh->query("COMMIT");
-
- $nbs = new NaiveBayesianStorage($_SESSION["uid"]);
- $nb = new NaiveBayesian($nbs);
- $nb->updateProbabilities();
- }
-
- function showArticleStats() {
- $article_id = (int) $_REQUEST["article_id"];
-
- $result = $this->dbh->query("SELECT score, guid, title, content FROM ttrss_entries, ttrss_user_entries WHERE ref_id = id AND id = " .
- $article_id . " AND owner_uid = " . $_SESSION["uid"]);
-
- if ($this->dbh->num_rows($result) != 0) {
- $guid = $this->dbh->fetch_result($result, 0, "guid");
- $title = $this->dbh->fetch_result($result, 0, "title");
-
- $content = mb_substr(mb_strtolower($title . " " . strip_tags($this->dbh->fetch_result($result, 0, "content"))), 0, $this->max_document_length);
-
- print "<h2>" . $title . "</h2>";
-
- $nbs = new NaiveBayesianStorage($_SESSION["uid"]);
- $nb = new NaiveBayesian($nbs);
-
- $categories = $nbs->getCategories();
-
- $ref = $nbs->getReference($guid, false);
-
- $current_cat = isset($ref["category_id"]) ? $categories[$ref["category_id"]]["category"] : "N/A";
-
- print "<p>" . T_sprintf("Currently stored as: %s", $current_cat) . "</p>";
-
- $result = $nb->categorize($content);
-
- print "<h3>" . __("Classifier result") . "</h3>";
-
- print "<table>";
- print "<tr><th>Category</th><th>Probability</th></tr>";
-
- foreach ($result as $k => $v) {
- print "<tr>";
- print "<td>" . $categories[$k]["category"] . "</td>";
- print "<td>" . $v . "</td>";
-
- print "</tr>";
- }
-
- print "</table>";
-
- } else {
- print_error("Article not found");
- }
-
- print "<div align='center'>";
-
- print "<button dojoType=\"dijit.form.Button\" onclick=\"return dijit.byId('bayesShowDlg').hide()\">".
- __('Close this window')."</button>";
-
- print "</div>";
-
- }
-
- function api_version() {
- return 2;
- }
-
-}
-?>
+++ /dev/null
- GNU GENERAL PUBLIC LICENSE
- Version 2, June 1991
-
- Copyright (C) 1989, 1991 Free Software Foundation, Inc.
- 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
- Everyone is permitted to copy and distribute verbatim copies
- of this license document, but changing it is not allowed.
-
- Preamble
-
- The licenses for most software are designed to take away your
-freedom to share and change it. By contrast, the GNU General Public
-License is intended to guarantee your freedom to share and change free
-software--to make sure the software is free for all its users. This
-General Public License applies to most of the Free Software
-Foundation's software and to any other program whose authors commit to
-using it. (Some other Free Software Foundation software is covered by
-the GNU Library General Public License instead.) You can apply it to
-your programs, too.
-
- When we speak of free software, we are referring to freedom, not
-price. Our General Public Licenses are designed to make sure that you
-have the freedom to distribute copies of free software (and charge for
-this service if you wish), that you receive source code or can get it
-if you want it, that you can change the software or use pieces of it
-in new free programs; and that you know you can do these things.
-
- To protect your rights, we need to make restrictions that forbid
-anyone to deny you these rights or to ask you to surrender the rights.
-These restrictions translate to certain responsibilities for you if you
-distribute copies of the software, or if you modify it.
-
- For example, if you distribute copies of such a program, whether
-gratis or for a fee, you must give the recipients all the rights that
-you have. You must make sure that they, too, receive or can get the
-source code. And you must show them these terms so they know their
-rights.
-
- We protect your rights with two steps: (1) copyright the software, and
-(2) offer you this license which gives you legal permission to copy,
-distribute and/or modify the software.
-
- Also, for each author's protection and ours, we want to make certain
-that everyone understands that there is no warranty for this free
-software. If the software is modified by someone else and passed on, we
-want its recipients to know that what they have is not the original, so
-that any problems introduced by others will not reflect on the original
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-
- Finally, any free program is threatened constantly by software
-patents. We wish to avoid the danger that redistributors of a free
-program will individually obtain patent licenses, in effect making the
-program proprietary. To prevent this, we have made it clear that any
-patent must be licensed for everyone's free use or not licensed at all.
-
- The precise terms and conditions for copying, distribution and
-modification follow.
- GNU GENERAL PUBLIC LICENSE
- TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
-
- 0. This License applies to any program or other work which contains
-a notice placed by the copyright holder saying it may be distributed
-under the terms of this General Public License. The "Program", below,
-refers to any such program or work, and a "work based on the Program"
-means either the Program or any derivative work under copyright law:
-that is to say, a work containing the Program or a portion of it,
-either verbatim or with modifications and/or translated into another
-language. (Hereinafter, translation is included without limitation in
-the term "modification".) Each licensee is addressed as "you".
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-Activities other than copying, distribution and modification are not
-covered by this License; they are outside its scope. The act of
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- 4. You may not copy, modify, sublicense, or distribute the Program
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-However, parties who have received copies, or rights, from you under
-this License will not have their licenses terminated so long as such
-parties remain in full compliance.
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- 5. You are not required to accept this License, since you have not
-signed it. However, nothing else grants you permission to modify or
-distribute the Program or its derivative works. These actions are
-prohibited by law if you do not accept this License. Therefore, by
-modifying or distributing the Program (or any work based on the
-Program), you indicate your acceptance of this License to do so, and
-all its terms and conditions for copying, distributing or modifying
-the Program or works based on it.
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- 6. Each time you redistribute the Program (or any work based on the
-Program), the recipient automatically receives a license from the
-original licensor to copy, distribute or modify the Program subject to
-these terms and conditions. You may not impose any further
-restrictions on the recipients' exercise of the rights granted herein.
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- 7. If, as a consequence of a court judgment or allegation of patent
-infringement or for any other reason (not limited to patent issues),
-conditions are imposed on you (whether by court order, agreement or
-otherwise) that contradict the conditions of this License, they do not
-excuse you from the conditions of this License. If you cannot
-distribute so as to satisfy simultaneously your obligations under this
-License and any other pertinent obligations, then as a consequence you
-may not distribute the Program at all. For example, if a patent
-license would not permit royalty-free redistribution of the Program by
-all those who receive copies directly or indirectly through you, then
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-refrain entirely from distribution of the Program.
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-such claims; this section has the sole purpose of protecting the
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-generous contributions to the wide range of software distributed
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-be a consequence of the rest of this License.
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-may add an explicit geographical distribution limitation excluding
-those countries, so that distribution is permitted only in or among
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- 9. The Free Software Foundation may publish revised and/or new versions
-of the General Public License from time to time. Such new versions will
-be similar in spirit to the present version, but may differ in detail to
-address new problems or concerns.
-
-Each version is given a distinguishing version number. If the Program
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-later version", you have the option of following the terms and conditions
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- NO WARRANTY
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-REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES,
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-TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY
-YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER
-PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
-POSSIBILITY OF SUCH DAMAGES.
-
- END OF TERMS AND CONDITIONS
-
+++ /dev/null
-2003/11/02 - Sortie de la version initiale 1.0
+++ /dev/null
-GNU GENERAL PUBLIC LICENSE
- Version 2, June 1991
-
- Copyright (C) 1989, 1991 Free Software Foundation, Inc., <http://fsf.org/>
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-any particular circumstance, the balance of the section is intended to
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-may add an explicit geographical distribution limitation excluding
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-address new problems or concerns.
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-either of that version or of any later version published by the Free
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- 10. If you wish to incorporate parts of the Program into other free
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-
- NO WARRANTY
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-FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN
-OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES
-PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED
-OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
-MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS
-TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE
-PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING,
-REPAIR OR CORRECTION.
-
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-WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
-REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES,
-INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING
-OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED
-TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY
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-PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
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- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU General Public License for more details.
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- This is free software, and you are welcome to redistribute it
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- `Gnomovision' (which makes passes at compilers) written by James Hacker.
-
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-library. If this is what you want to do, use the GNU Lesser General
-Public License instead of this License.
+++ /dev/null
-PHP Naive Bayesian Filter
-============================================================
-This library implements Naive Bayes classifier. Original Project developed by Loic d'Anterroches [loic xhtml.net]. This Library is very Usefull but is not Published now. so Salvage from [Internet Archive] and create Github Repositry.
-
-see more information to Original Readme.txt and [Original Page].
-And If there is a problem with the publication of this repository, I will close this repository.
-
-
-[loic xhtml.net]: <http://www.xhtml.net/php/PHPNaiveBayesianFilter>
-[Internet Archive]: <https://archive.org/>
-[Original Page]: <https://web.archive.org/web/20111211215027/http://www.xhtml.net/php/PHPNaiveBayesianFilter>
-
-Writing by Japanese
-------------------------------------------------------------
-このライブラリは単純ベイズ分類器を実装したライブラリです。元のプロジェクトはLoic d'Anterrochesが作成しています。非常に有益なライブラリですが、現在は公開されていないようです。そこでインターネットアーカイブからライブラリをサルベージし、Githubのレポジトリを作成しました。
-
-より詳しい情報はオリジナルのReadme.txtを参照してください。
-もし、このレポジトリの公開に問題があるようならば、このレポジトリを削除します。
-
-extract Original Readme
-------------------------------------------------------------
-> This file is part of PHP Naive Bayesian Filter.
->
-> The Initial Developer of the Original Code is
-> Loic d'Anterroches [loic xhtml.net].
-> Portions created by the Initial Developer are Copyright (C) 2003
-> the Initial Developer. All Rights Reserved.
->
-> PHP Naive Bayesian Filter is free software; you can redistribute it
-> and/or modify it under the terms of the GNU General Public License as
-> published by the Free Software Foundation; either version 2 of
-> the License, or (at your option) any later version.
->
-> PHP Naive Bayesian Filter is distributed in the hope that it will
-> be useful, but WITHOUT ANY WARRANTY; without even the implied
-> warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
-> See the GNU General Public License for more details.
->
-> You should have received a copy of the GNU General Public License
-> along with Foobar; if not, write to the Free Software
-> Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
\ No newline at end of file
+++ /dev/null
-/*
- ***** BEGIN LICENSE BLOCK *****
- This file is part of PHP Naive Bayesian Filter.
-
- The Initial Developer of the Original Code is
- Loic d'Anterroches [loic xhtml.net].
- Portions created by the Initial Developer are Copyright (C) 2003
- the Initial Developer. All Rights Reserved.
-
- PHP Naive Bayesian Filter is free software; you can redistribute it
- and/or modify it under the terms of the GNU General Public License as
- published by the Free Software Foundation; either version 2 of
- the License, or (at your option) any later version.
-
- PHP Naive Bayesian Filter is distributed in the hope that it will
- be useful, but WITHOUT ANY WARRANTY; without even the implied
- warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
- See the GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with Foobar; if not, write to the Free Software
- Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
-
- ***** END LICENSE BLOCK *****
-*/
-
-
-** Presentation **
-
-Voici une implementation generale d'un filtre reposant sur le theoreme de Bayes.
-L'application la plus connue est le filtre anti-spam. Vous pouvez aussi
-l'utiliser pour faire de la classification automatique de documents.
-
-Ce programme se base sur la version simplifiee du theoreme de Bayes comme
-decrite par Ken Williams, ken@mathforum.org sur la page
-http://mathforum.org/~ken/bayes/bayes.html au 31/10/2003.
-
-Le systeme permet de maniere generale de faire la classification de documents
-textes dans differentes categories. Si vous voulez l'utiliser pour une
-classification de vos messages entre spam et non-spam, alors il vous faudra 2
-categories, une "spam" et une "nonspam".
-
-J'ai cree ce script car c'est une sujet a la mode en ce moment. Particulierement
-pour filtrer les commentaires et les trackbacks dans les blogs. Le systeme
-propose ici permet d'avoir plus que deux categories spam et non spam. Cela permet
-donc theoriquement de l'utiliser pour la classification dans de multiples
-categories.
-
-Un petit script 'index.php' vous permet de tester le systeme, ensuite vous
-pouvez inclure la classe dans vos scripts. Les fichiers class.naivebayesian.php
-et class.naivebayesianstorage.php peuvent aussi etre utilises avec la licence
-GNU Lesser General Public License Version 2.1 ou ulterieure.
-
-
-** Fonctionnalites **
-
-- Une classe avec la logique de base, une autre qui est l'interface de stockage.
-- Stockage des donnees dans une base de données pour le moment MySQL mais
-vous pouvez utiliser celle que vous voulez via l'interface de stockage.
-- Apprentissage
-- Desapprentissage
-- Archivage automatique des documents "reference"
-- L'interface de stockage par defaut utilise MySQL et repose sur deux classes
-d'Olivier Meunier.
-
-** Utilisation **
-
-Regardez le code de index.php
-Pour une bonne utilisation il vous faut creer une autre classe qui herite de
-NaiveBayesian pour avoir votre propre fonction pour ignorer les mots qui ne
-portent pas de sens particulier. Ceci n'est pas fait dans 'index.php'
-
-class votreclass extends NaiveBayesian
-{
- function getIgnoreList()
- {
- return array('the', 'that', 'you', 'for', 'and');
- }
-}
-
-
-** Des questions **
-
-Pouvez me contacter par email a loic xhtml.net, ou venir sur http://www.xhtml.net/
-
-
+++ /dev/null
-<?php
- /*
- ***** BEGIN LICENSE BLOCK *****
- This file is part of PHP Naive Bayesian Filter.
-
- The Initial Developer of the Original Code is
- Loic d'Anterroches [loic_at_xhtml.net].
- Portions created by the Initial Developer are Copyright (C) 2003
- the Initial Developer. All Rights Reserved.
-
- Contributor(s):
- See the source
-
- PHP Naive Bayesian Filter is free software; you can redistribute it
- and/or modify it under the terms of the GNU General Public License as
- published by the Free Software Foundation; either version 2 of
- the License, or (at your option) any later version.
-
- PHP Naive Bayesian Filter is distributed in the hope that it will
- be useful, but WITHOUT ANY WARRANTY; without even the implied
- warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
- See the GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with Foobar; if not, write to the Free Software
- Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
-
- Alternatively, the contents of this file may be used under the terms of
- the GNU Lesser General Public License Version 2.1 or later (the "LGPL"),
- in which case the provisions of the LGPL are applicable instead
- of those above.
-
- ***** END LICENSE BLOCK *****
- */
-
- class NaiveBayesian {
- /** min token length for it to be taken into consideration */
- var $min_token_length = 3;
- /** max token length for it to be taken into consideration */
- var $max_token_length = 15;
- /** list of token to ignore
- @see getIgnoreList()
- */
- var $ignore_list = array();
- /** storage object
- @see class NaiveBayesianStorage
- */
- var $nbs = null;
-
- function NaiveBayesian($nbs) {
- $this->nbs = $nbs;
-
- return true;
- }
-
- /** categorize a document.
- Get list of categories in which the document can be categorized
- with a score for each category.
-
- @return array keys = category ids, values = scores
- @param string document
- */
- function categorize($document) {
- $scores = array();
- $categories = $this->nbs->getCategories();
- $tokens = $this->_getTokens($document);
-
- // calculate the score in each category
- $total_words = 0;
- $ncat = 0;
-
- while (list($category, $data) = each($categories)) {
- $total_words += $data['word_count'];
- $ncat++;
- }
-
- reset($categories);
-
- while (list($category, $data) = each($categories)) {
- $scores[$category] = $data['probability'];
- // small probability for a word not in the category
- // maybe putting 1.0 as a 'no effect' word can also be good
-
- if ($data['word_count'] > 0)
- $small_proba = 1.0 / ($data['word_count'] * 2);
- else
- $small_proba = 0;
-
- reset($tokens);
-
- while (list($token, $count) = each($tokens)) {
-
- if ($this->nbs->wordExists($token)) {
- $word = $this->nbs->getWord($token, $category);
-
- if ($word['count']) {
- $proba = $word['count'] / $data['word_count'];
- }
- else {
- $proba = $small_proba;
- }
-
- $scores[$category] *= pow($proba, $count) * pow($total_words / $ncat, $count);
- // pow($total_words/$ncat, $count) is here to avoid underflow.
-
- }
- }
- }
-
- return $this->_rescale($scores);
- }
-
- /** training against a document.
- Set a document as being in a specific category. The document becomes a reference
- and is saved in the table of references. After a set of training is done
- the updateProbabilities() function must be run.
-
- @see updateProbabilities()
- @see untrain()
- @return bool success
- @param string document id, must be unique
- @param string category_id the category id in which the document should be
- @param string content of the document
- */
- function train($doc_id, $category_id, $content) {
- $ret = false;
-
-
- // if this doc_id already trained, no trained
- if (!$this->nbs->getReference($doc_id, false)) {
-
- $tokens = $this->_getTokens($content);
-
- while (list($token, $count) = each($tokens)) {
- $this->nbs->updateWord($token, $count, $category_id);
- }
-
- $this->nbs->saveReference($doc_id, $category_id, $content);
-
- $ret = true;
- }
- else {
- $ret = false;
- }
-
- return $ret;
- }
-
- /** untraining of a document.
- To remove just one document from the references.
-
- @see updateProbabilities()
- @see untrain()
- @return bool success
- @param string document id, must be unique
- */
- function untrain($doc_id) {
- $ref = $this->nbs->getReference($doc_id);
-
- if (isset($ref['content'])) {
-
- $tokens = $this->_getTokens($ref['content']);
-
- while (list($token, $count) = each($tokens)) {
- $this->nbs->removeWord($token, $count, $ref['category_id']);
- }
-
- $this->nbs->removeReference($doc_id);
-
- return true;
- } else {
- return false;
- }
- }
-
- /** rescale the results between 0 and 1.
-
- @author Ken Williams, ken@mathforum.org
- @see categorize()
- @return array normalized scores (keys => category, values => scores)
- @param array scores (keys => category, values => scores)
- */
- function _rescale($scores) {
- // Scale everything back to a reasonable area in
- // logspace (near zero), un-loggify, and normalize
- $total = 0.0;
- $max = 0.0;
- reset($scores);
-
- while (list($cat, $score) = each($scores)) {
- if ($score >= $max)
- $max = $score;
- }
-
- reset($scores);
- while (list($cat, $score) = each($scores)) {
- $scores[$cat] = (float) exp($score - $max);
- $total += (float) pow($scores[$cat], 2);
- }
-
- $total = (float) sqrt($total);
-
- reset($scores);
- while (list($cat, $score) = each($scores)) {
- $scores[$cat] = (float) $scores[$cat] / $total;
- }
- reset($scores);
-
- return $scores;
- }
-
- /** update the probabilities of the categories and word count.
- This function must be run after a set of training
-
- @see train()
- @see untrain()
- @return bool sucess
- */
- function updateProbabilities() {
- // this function is really only database manipulation
- // that is why all is done in the NaiveBayesianStorage
- return $this->nbs->updateProbabilities();
- }
-
- /** Get the list of token to ignore.
- @return array ignore list
- */
- function getIgnoreList() {
- //return array('the', 'that', 'you', 'for', 'and');
-
- // https://en.wikipedia.org/wiki/Most_common_words_in_English
- return array('the', 'be', 'to', 'of', 'and', 'a', 'in', 'that', 'have', 'I', 'it', 'for', 'not', 'on', 'with',
- 'he', 'as', 'you', 'do', 'at', 'this', 'but', 'his', 'by', 'from', 'they', 'we', 'say', 'her',
- 'she', 'or', 'an', 'will', 'my', 'one', 'all', 'would', 'there', 'their', 'what', 'so', 'up',
- 'out', 'if', 'about', 'who', 'get', 'which', 'go', 'me', 'when', 'make', 'can', 'like', 'time',
- 'no', 'just', 'him', 'know', 'take', 'people', 'into', 'year', 'your', 'good', 'some', 'could',
- 'them', 'see', 'other', 'than', 'then', 'now', 'look', 'only', 'come', 'its', 'over', 'think',
- 'also', 'back', 'after', 'use', 'two', 'how', 'our', 'work', 'first', 'well', 'way', 'even',
- 'new', 'want', 'because', 'any', 'these', 'give', 'day', 'most', 'us', 'read', 'more');
-
- }
-
- /** get the tokens from a string
-
- @author James Seng. [http://james.seng.cc/] (based on his perl version)
-
- @return array tokens
- @param string the string to get the tokens from
- */
- function _getTokens($string) {
- $rawtokens = array();
- $tokens = array();
- //$string = $this->_cleanString($string);
-
- if (count(0 >= $this->ignore_list)) {
- $this->ignore_list = $this->getIgnoreList();
- }
-
- $rawtokens = preg_split("/[\(\),:\.;\t\r\n ]/", $string, -1, PREG_SPLIT_NO_EMPTY);
-
- // remove some tokens
- while (list(, $token) = each($rawtokens)) {
- $token = trim($token);
- if (!(('' == $token) || (mb_strpos($token, "&") !== FALSE) || (mb_strlen($token) < $this->min_token_length) || (mb_strlen($token) > $this->max_token_length) || (preg_match('/^[0-9]+$/', $token)) || (in_array($token, $this->ignore_list)))) {
- $tokens[$token]++;
- }
- }
-
- return $tokens;
- }
-
- /** clean a string from the diacritics
-
- @author Antoine Bajolet [phpdig_at_toiletoine.net]
- @author SPIP [http://uzine.net/spip/]
-
- @return string clean string
- @param string string with accents
- */
- function _cleanString($string) {
- $diac = /* A */ chr(192) . chr(193) . chr(194) . chr(195) . chr(196) . chr(197) .
- /* a */ chr(224) . chr(225) . chr(226) . chr(227) . chr(228) . chr(229) .
- /* O */ chr(210) . chr(211) . chr(212) . chr(213) . chr(214) . chr(216) .
- /* o */ chr(242) . chr(243) . chr(244) . chr(245) . chr(246) . chr(248) .
- /* E */ chr(200) . chr(201) . chr(202) . chr(203) .
- /* e */ chr(232) . chr(233) . chr(234) . chr(235) .
- /* Cc */ chr(199) . chr(231) .
- /* I */ chr(204) . chr(205) . chr(206) . chr(207) .
- /* i */ chr(236) . chr(237) . chr(238) . chr(239) .
- /* U */ chr(217) . chr(218) . chr(219) . chr(220) .
- /* u */ chr(249) . chr(250) . chr(251) . chr(252) .
- /* yNn */ chr(255) . chr(209) . chr(241);
-
- return strtolower(strtr($string, $diac, 'AAAAAAaaaaaaOOOOOOooooooEEEEeeeeCcIIIIiiiiUUUUuuuuyNn'));
- }
-
- }
+++ /dev/null
-<?php
-
- class NaiveBayesianNgram extends NaiveBayesian {
- var $N = 2;
-
- /**
- * add Parameter for ngram
- *
- * @param NaiveBayesianStorage $nbs
- * @param ngram's N $n
- * @return boolean
- */
- function __construct($nbs, $n = 2) {
- parent::__construct($nbs);
-
- $this->N = $n;
-
- return true;
- }
-
- /**
- * override method for ngram
- *
- * @param string $string
- * @return multiple
- */
- function _getTokens($string) {
- $tokens = array();
-
- if (mb_strlen($string)) {
- for ($i = 0; $i < mb_strlen($string) - $this->N; $i++) {
- $wd = mb_substr($string, $i, $this->N);
-
- if (mb_strlen($wd) == $this->N) {
- if (!array_key_exists($wd, $tokens)) {
- $tokens[$wd] = 0;
- }
-
- $tokens[$wd]++;
- }
- }
- }
-
- if (count($tokens)) {
- // remove empty value
- $tokens = array_filter($tokens);
- }
-
- return $tokens;
- }
-
- }
+++ /dev/null
-<?php
- /*
- ***** BEGIN LICENSE BLOCK *****
- This file is part of PHP Naive Bayesian Filter.
-
- The Initial Developer of the Original Code is
- Loic d'Anterroches [loic_at_xhtml.net].
- Portions created by the Initial Developer are Copyright (C) 2003
- the Initial Developer. All Rights Reserved.
-
- Contributor(s):
-
- PHP Naive Bayesian Filter is free software; you can redistribute it
- and/or modify it under the terms of the GNU General Public License as
- published by the Free Software Foundation; either version 2 of
- the License, or (at your option) any later version.
-
- PHP Naive Bayesian Filter is distributed in the hope that it will
- be useful, but WITHOUT ANY WARRANTY; without even the implied
- warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
- See the GNU General Public License for more details.
-
- You should have received a copy of the GNU General Public License
- along with Foobar; if not, write to the Free Software
- Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
-
- Alternatively, the contents of this file may be used under the terms of
- the GNU Lesser General Public License Version 2.1 or later (the "LGPL"),
- in which case the provisions of the LGPL are applicable instead
- of those above.
-
- ***** END LICENSE BLOCK *****
- */
-
- /** Access to the storage of the data for the filter.
-
- To avoid dependency with respect to any database, this class handle all the
- access to the data storage. You can provide your own class as long as
- all the methods are available. The current one rely on a MySQL database.
-
- methods:
- - array getCategories()
- - bool wordExists(string $word)
- - array getWord(string $word, string $categoryid)
-
- */
- class NaiveBayesianStorage {
- var $con = null;
- var $owner_uid = null;
- var $max_document_length = 3000; // classifier can't rescale output for very long strings apparently
-
- function NaiveBayesianStorage($owner_uid) {
- $this->con = Db::get();
- $this->owner_uid = $owner_uid;
-
- return true;
- }
-
- /** get the list of categories with basic data.
-
- @return array key = category ids, values = array(keys = 'probability', 'word_count')
- */
- function getCategories() {
- $categories = array();
- $rs = $this->con->query('SELECT * FROM ttrss_plugin_af_sort_bayes_categories WHERE owner_uid = ' . $this->owner_uid);
-
- while ($line = $this->con->fetch_assoc($rs)) {
- $categories[$line['id']] = array('probability' => $line['probability'],
- 'category' => $line['category'],
- 'word_count' => $line['word_count']
- );
- }
-
- return $categories;
- }
-
- function getCategoryByName($category) {
- $rs = $this->con->query("SELECT id FROM ttrss_plugin_af_sort_bayes_categories WHERE category = '" .
- $this->con->escape_string($category) . "' AND owner_uid = " . $this->owner_uid);
-
- if ($this->con->num_rows($rs) != 0) {
- return $this->con->fetch_result($rs, 0, "id");
- }
-
- return false;
- }
-
- function getCategoryById($category_id) {
- $rs = $this->con->query("SELECT category FROM ttrss_plugin_af_sort_bayes_categories WHERE id = '" .
- (int)$category_id . "' AND owner_uid = " . $this->owner_uid);
-
- if ($this->con->num_rows($rs) != 0) {
- return $this->con->fetch_result($rs, 0, "category");
- }
-
- return false;
- }
-
- /** see if the word is an already learnt word.
- @return bool
- @param string word
- */
- function wordExists($word) {
- $rs = $this->con->query("SELECT * FROM ttrss_plugin_af_sort_bayes_wordfreqs WHERE word='" . $this->con->escape_string($word) . "' AND
- owner_uid = " . $this->owner_uid);
-
- return $this->con->num_rows($rs) != 0;
- }
-
- /** get details of a word in a category.
- @return array ('count' => count)
- @param string word
- @param string category id
- */
- function getWord($word, $category_id) {
- $details = array();
-
- $rs = $this->con->query("SELECT * FROM ttrss_plugin_af_sort_bayes_wordfreqs WHERE word='" .
- $this->con->escape_string($word) . "' AND category_id=" . (int)$category_id);
-
- if ($this->con->num_rows($rs) == 0 ) {
- $details['count'] = 0;
- } else {
- $details['count'] = $this->con->fetch_result($rs, 0, "count");
- }
-
- return $details;
- }
-
- /** update a word in a category.
- If the word is new in this category it is added, else only the count is updated.
-
- @return bool success
- @param string word
- @param int count
- @paran string category id
- */
- function updateWord($word, $count, $category_id) {
- $oldword = $this->getWord($word, $category_id);
-
- if (0 == $oldword['count']) {
- return $this->con->query("INSERT INTO ttrss_plugin_af_sort_bayes_wordfreqs (word, category_id, count, owner_uid)
- VALUES ('" . $this->con->escape_string($word) . "', '" .
- (int)$category_id . "', '" .
- (int)$count . "', '".
- $this->owner_uid . "')");
- }
- else {
- return $this->con->query("UPDATE ttrss_plugin_af_sort_bayes_wordfreqs SET count = count + " . (int) $count . " WHERE category_id = '" . $this->con->escape_string($category_id) . "' AND word = '" . $this->con->escape_string($word) . "'");
- }
- }
-
- /** remove a word from a category.
-
- @return bool success
- @param string word
- @param int count
- @param string category id
- */
- function removeWord($word, $count, $category_id) {
- $oldword = $this->getWord($word, $category_id);
-
- if (0 != $oldword['count'] && 0 >= ($oldword['count'] - $count)) {
- return $this->con->query("DELETE FROM ttrss_plugin_af_sort_bayes_wordfreqs WHERE word='" .
- $this->con->escape_string($word) . "' AND category_id='" .
- $this->con->escape_string($category_id) . "'");
- }
- else {
- return $this->con->query("UPDATE ttrss_plugin_af_sort_bayes_wordfreqs SET count = count - " .
- (int) $count . " WHERE category_id = '" . $this->con->escape_string($category_id) . "'
- AND word = '" . $this->con->escape_string($word) . "'");
- }
- }
-
- /** update the probabilities of the categories and word count.
- This function must be run after a set of training
-
- @return bool sucess
- */
- function updateProbabilities() {
- // first update the word count of each category
- $rs = $this->con->query("SELECT SUM(count) AS total FROM ttrss_plugin_af_sort_bayes_wordfreqs WHERE owner_uid = ".$this->owner_uid);
-
- $total_words = $this->con->fetch_result($rs, 0, "total");
-
- if ($total_words == 0) {
- $this->con->query("UPDATE ttrss_plugin_af_sort_bayes_categories SET word_count=0, probability=0 WHERE owner_uid = " . $this->owner_uid);
- return true;
- }
-
- $rs = $this->con->query("SELECT tc.id AS category_id, SUM(count) AS total FROM ttrss_plugin_af_sort_bayes_categories AS tc
- LEFT JOIN ttrss_plugin_af_sort_bayes_wordfreqs AS tw ON (tc.id = tw.category_id) WHERE tc.owner_uid = ".$this->owner_uid." GROUP BY tc.id");
-
- while ($line = $this->con->fetch_assoc($rs)) {
-
- $proba = (int)$line['total'] / $total_words;
- $this->con->query("UPDATE ttrss_plugin_af_sort_bayes_categories SET word_count=" . (int) $line['total'] .
- ", probability=" . $proba . " WHERE id = '" . $line['category_id'] . "'");
- }
-
- return true;
- }
-
- /** save a reference in the database.
-
- @return bool success
- @param string reference if, must be unique
- @param string category id
- @param string content of the reference
- */
- function saveReference($doc_id, $category_id, $content) {
- return $this->con->query("INSERT INTO ttrss_plugin_af_sort_bayes_references (document_id, category_id, owner_uid) VALUES
- ('" . $this->con->escape_string($doc_id) . "', '" .
- (int)$category_id . "', " .
- (int)$this->owner_uid . ")");
- }
-
- /** get a reference from the database.
-
- @return array reference( category_id => ...., content => ....)
- @param string id
- */
- function getReference($doc_id, $include_content = true)
- {
-
- $ref = array();
- $rs = $this->con->query("SELECT * FROM ttrss_plugin_af_sort_bayes_references WHERE document_id='" .
- $this->con->escape_string($doc_id) . "' AND owner_uid = " . $this->owner_uid);
-
- if ($this->con->num_rows($rs) == 0) {
- return $ref;
- }
-
- $ref['category_id'] = $this->con->fetch_result($rs, 0, 'category_id');
- $ref['id'] = $this->con->fetch_result($rs, 0, 'id');
- $ref['document_id'] = $this->con->fetch_result($rs, 0, 'document_id');
-
- if ($include_content) {
- $rs = $this->con->query("SELECT content, title FROM ttrss_entries WHERE guid = '" .
- $this->con->escape_string($ref['document_id']) . "'");
-
- if ($this->con->num_rows($rs) != 0) {
- $ref['content'] = mb_substr(mb_strtolower($this->con->fetch_result($rs, 0, 'title') . ' ' . strip_tags($this->con->fetch_result($rs, 0, 'content'))), 0,
- $this->max_document_length);
- }
- }
-
- return $ref;
- }
-
- /** remove a reference from the database
-
- @return bool sucess
- @param string reference id
- */
- function removeReference($doc_id) {
-
- return $this->con->query("DELETE FROM ttrss_plugin_af_sort_bayes_references WHERE document_id='" . $this->con->escape_string($doc_id) . "' AND owner_uid = " . $this->owner_uid);
- }
-
- }
projects / tt-rss.git / commitdiff
