The simplest way to detect names in a document is to use a name list...

The simplest way to detect names in a document is to use a name list, and when the Tokenizer extracts a word it compares it against this list. But this solution is not effective since we need to add all names in this list, as well; it cannot deal with the compound names. Stemming The main goal of the stemming is toimprove the efficiency of the classification by reducing the number of terms being input to the classification.

As we mentioned earlier, Arabic language is highly derivative where tens or even hundreds of words could be formed using only one stem, furthermore, a single word may be derived from multiple stem. So, working with Arabic document words without stemming results in an enormous number of words are being input to the classification phase. This will definitely increase the classifier complexity and reduce its scalability. Many stemming methods havebeen developed for Arabic language.

These stemmers are classified intotwo categories. The first one is root extraction stemmerlike the stemmer introduced by[^11] The secondis light stemmers like the stemmer introduced by in[^12] .

In this project we used a Rule-Based Light Stemmer introduced in[^13] In this stemmer, to solves the problem of prefix/suffix sequenceambiguity, words are firstly matched against a set of all possible word patterns in Arabic before prefix/suffix truncation, so if a word starts with apossible prefix but itmatched one of the possible patterns, then it’s a validword and this prefix is part of the originaland should not be truncated.

Then, if the word didn’t match any of thepatterns, then the compatibilitybetween the prefix and suffix should be found, where some suffixescould not be combined with certain suffixes in thesame word. If the prefix and suffix are combatable then they could be removed from this word.

For example the prefix “ ال ”may not be combined with the suffix “ ك ” so we cannot say “ الكتابك ” and thus if we have a word like“ الكرنك ” the stemmer will not remove the prefix and suffixwhich lead to the wrong word “ كرن ” but it willdetect that the last character “ ك ” is part of theoriginal word and not a suffix, and soit will onlyremove the prefix “ ال ” which will lead to the correctstem “ كرنك” If the combination of the prefix and suffix is validthen the stemmer counts the letters of the word after removingthe prefix and suffix since Arabic words other thanconjunctions like “ من” ،“في ” consists of at least 3characters.