World Wide Tutorial

Preamble
My thinking is not new - I started this kind of work before SQL Server does this kind of service - and have continued recently with projects in my company.
Here, then these elements together in this document and I hope you enjoy reading this.
Some definitions

All developers know the meaning of the word syntax (well, good developers ...!).
I would therefore do not insult our readers recall the notice of the small nor the large Robert Larousse ...
Semantics
Knowing the meaning of the word semantics is less widespread, especially since it depends on the meaning of words therefore semantics ... Far from being a tautology and although this gibberish inevitably tends to make you smile, I just like to point the intellect whole exercise has difficulty distinguishing between semantics and syntax ...

I do not give a definition by opposition of semantics, saying that if the syntax is responsible for grammar, semantics, it takes care of meaning, it means that my words and phrases want to say, in other words, ideas they convey.

1. Indexing base
1.1. Keywords and index
This is an old method widely used in documents issued in paper form. There are two different modes: the abstract and index still called thesaurus.
The abstracts are generally used in legal documentation and are placed on top of the document often in the title. They allow, before reading the publication, to know the legal context, that is to say about what are treated. It is essentially words or phrases, sentences rarely.

The index is usually a list of some carefully chosen words, or all own name cited in a document, with a reference for each page or is this word or proper name.
The index is usually a list of some carefully chosen words, or all own name cited in a document, with a reference for each page or is this word or proper name.
We can now proceed to food at the table of words, only by the words chosen:

insert into KEYWORD (MOT_ID, MOT_MOT) values (1, 'small'); insert into KEYWORD (MOT_ID, MOT_MOT) values (2, 'chat'); insert into KEYWORD (MOT_ID, MOT_MOT) values (3, 'is') ; Insert into KEYWORD (MOT_ID, MOT_MOT) values (4, 'death'); insert into KEYWORD (MOT_ID, MOT_MOT) values (5, 'fact'); insert into KEYWORD (MOT_ID, MOT_MOT) values (6, 'beautiful' ); Insert into KEYWORD (MOT_ID, MOT_MOT) values (7, 'sun'); insert into KEYWORD (MOT_ID, MOT_MOT) values (8, 'shining'); insert into KEYWORD (MOT_ID, MOT_MOT) values (9, birds '); Insert into KEYWORD (MOT_ID, MOT_MOT) values (10,' sing '); insert into KEYWORD (MOT_ID, MOT_MOT) values (11,' understand '); insert into KEYWORD (MOT_ID, MOT_MOT) values (12,' undertake '); insert into KEYWORD (MOT_ID, MOT_MOT) values (13,' udders'); insert into KEYWORD (MOT_ID, MOT_MOT) values (14, 'trade'); insert into KEYWORD (MOT_ID, MOT_MOT) values (15, 'take'); insert into KEYWORD (MOT_ID, MOT_MOT) values (16, 'time'); insert into KEYWORD (MOT_ID, MOT_MOT) values (17, 'live'); insert into KEYWORD (MOT_ID, MOT_MOT) values (18 , 'Saying'); insert into KEYWORD (MOT_ID, MOT_MOT) values (19, 'other'); insert into KEYWORD (MOT_ID, MOT_MOT) values (20, 'life'); insert into KEYWORD (MOT_ID, MOT_MOT) values ( 21, 'high'); insert into KEYWORD (MOT_ID, MOT_MOT) values (22, 'low'); insert into KEYWORD (MOT_ID, MOT_MOT) values (23, 'confused'); insert into KEYWORD (MOT_ID, MOT_MOT) values (24, 'low'); insert into KEYWORD (MOT_ID, MOT_MOT) values (25, 'Guitar'); insert into KEYWORD (MOT_ID, MOT_MOT) values (26, 'bass'); insert into KEYWORD (MOT_ID, MOT_MOT) values (27, 'violin'); insert into KEYWORD (MOT_ID, MOT_MOT) values (28, 'must'); insert into KEYWORD (MOT_ID, MOT_MOT) values (29, 'eat'); insert into KEYWORD (MOT_ID, MOT_MOT ) Values (30, 'from'); insert into KEYWORD (MOT_ID, MOT_MOT) values (31, 'dying'); insert into KEYWORD (MOT_ID, MOT_MOT) values (32, 'little'); insert into KEYWORD (MOT_ID, MOT_MOT) values (33, 'end'); insert into KEYWORD (MOT_ID, MOT_MOT) values (34, 'caution'); insert into KEYWORD (MOT_ID, MOT_MOT) values (35, 'mere'); insert into KEYWORD (MOT_ID , MOT_MOT) values (36, 'security'); insert into KEYWORD (MOT_ID, MOT_MOT) values (37, 'boys);

Last phase of our algorithm, seize correspondence between words and texts in the table INDEX:

insert into INDEX (TXT_ID, MOT_ID) values (1, 1); insert into INDEX (TXT_ID, MOT_ID) values (1, 2); insert into INDEX (TXT_ID, MOT_ID) values (1, 3); insert into INDEX (TXT_ID , MOT_ID) values (1, 4); insert into INDEX (TXT_ID, MOT_ID) values (2, 5); insert into INDEX (TXT_ID, MOT_ID) values (2, 6); insert into INDEX (TXT_ID, MOT_ID) values ( 2, 7); insert into INDEX (TXT_ID, MOT_ID) values (2, 8); insert into INDEX (TXT_ID, MOT_ID) values (2, 9); insert into INDEX (TXT_ID, MOT_ID) values (2, 10); insert into INDEX (TXT_ID, MOT_ID) values (3, 11); insert into INDEX (TXT_ID, MOT_ID) values (3, 12); insert into INDEX (TXT_ID, MOT_ID) values (3, 13); insert into INDEX (TXT_ID , MOT_ID) values (3, 14); insert into INDEX (TXT_ID, MOT_ID) values (4, 15); insert into INDEX (TXT_ID, MOT_ID) values (4, 16); insert into INDEX (TXT_ID, MOT_ID) values ( 4, 17); insert into INDEX (TXT_ID, MOT_ID) values (4, 18); insert into INDEX (TXT_ID, MOT_ID) values (4, 19); insert into INDEX (TXT_ID, MOT_ID) values (5, 20); insert into INDEX (TXT_ID, MOT_ID) values (5, 21); insert into INDEX (TXT_ID, MOT_ID) values (5, 22); insert into INDEX (TXT_ID, MOT_ID) values (6, 23); insert into INDEX (TXT_ID , MOT_ID) values (6, 24); insert into INDEX (TXT_ID, MOT_ID) values (6, 25); insert into INDEX (TXT_ID, MOT_ID) values (6, 26); insert into INDEX (TXT_ID, MOT_ID) values ( 6, 27); insert into INDEX (TXT_ID, MOT_ID) values (7, 17); insert into INDEX (TXT_ID, MOT_ID) values (7, 28); insert into INDEX (TXT_ID, MOT_ID) values (7, 29); insert into INDEX (TXT_ID, MOT_ID) values (8, 30); insert into INDEX (TXT_ID, MOT_ID) values (8, 31); insert into INDEX (TXT_ID, MOT_ID) values (8, 32); insert into INDEX (TXT_ID , MOT_ID) values (9, 4); insert into INDEX (TXT_ID, MOT_ID) values (9, 18); insert into INDEX (TXT_ID, MOT_ID) values (9, 33); insert into INDEX (TXT_ID, MOT_ID) values ( 10, 3); insert into INDEX (TXT_ID, MOT_ID) values (10, 34); insert into INDEX (TXT_ID, MOT_ID) values (10, 35); insert into INDEX (TXT_ID, MOT_ID) values (10, 36); insert into INDEX (TXT_ID, MOT_ID) values (10, 37);

1.2.3. The complaints
It is a matter of finding applications to be implemented to respond to the text search.
A good way to solve the thing would be to find a single complaint could handle the majority of cases. For example, set a single complaint able to search a text containing:
a word or another ( 'LIVING' or 'EAT' or both)
a word and another ( 'LIVE' and 'EAT')
three or more words ( 'LOW' and 'GUITAR' and 'BASS')
at least two out of three words (of 'Death', 'SELF', 'LIVE')!
etc. ...
Text OR

Search text containing a word or another: 'LIVE' or 'EAT' (or both)

select distinct from t.TXT_ID TEXT t join d on t.TXT_ID INDEX = d.TXT_ID join MOT m on d.MOT_ID = m.MOT_ID where m.MOT_MOT in ( 'LIVING', 'EAT')

AND complaint

Search text containing a word and another: 'LIVE' and 'EAT'
The complaint is based on the same motion as before, with the addition of a clause aggregation with a grouping:

select distinct from t.TXT_ID TEXT t join d on t.TXT_ID INDEX = d.TXT_ID join MOT m on d.MOT_ID = m.MOT_ID where m.MOT_MOT in ( 'LIVING', 'EAT') group by having t.TXT_ID count (*)> = 2

Search text containing three words: 'LOW' and 'GUITAR' and 'BASS'

select distinct from t.TXT_ID TEXT t join d on t.TXT_ID INDEX = d.TXT_ID join MOT m on d.MOT_ID = m.MOT_ID where m.MOT_MOT in ( 'LOW', 'GUITAR', 'BASS') group by t.TXT_ID having count (*)> = 3

application combining OR and AND

Search text containing at least two words on 3, one of 'Death', 'SELF', 'LIVING'

select distinct from t.TXT_ID TEXT t join d on t.TXT_ID INDEX = d.TXT_ID join MOT m on d.MOT_ID = m.MOT_ID where m.MOT_MOT in ( 'Death', 'SELF', 'LIVE') group by t.TXT_ID having count (*)> = 2

widespread application configurable

In general:

select distinct from t.TXT_ID TEXT t join d on t.TXT_ID INDEX = d.TXT_ID join MOT m on d.MOT_ID = m.MOT_ID where m.MOT_MOT in (: param1) group by having t.TXT_ID count (*)> =: Param2
or:
: param1 is a list of words separated by commas
: param2 the number of occurrence of the word required simultaneously
Thus the first complaint (OR with two words) can be expressed:

select distinct from t.TXT_ID TEXT t join d on t.TXT_ID INDEX = d.TXT_ID join MOT m on d.MOT_ID = m.MOT_ID where m.MOT_MOT in ( 'LIVING', 'EAT') group by having t.TXT_ID count (*)> = 1