A program library based on the Naturel Query Language!
After eight years of research and development, AGIR introduces
NQL, a new technology that allows you to integrate a powerful text search engine in your software solutions. Featuring the use of a natural language,
NQL breaks through the technical limitations of Boolean logic and solves a number of problems related to the processing of large volumes of information.
NQL incorporates several new concepts that improve the performance of full text and structured searches.
NQL is a C++ programming library available for full text search. It uses a very powerful algorithm that allows users to query the database using a natural (or common) language, no boolean operators are required.
The engine uses a statistical analysis to sort the documents in order or relevance. To sort, it uses factors such as presence of the terms, automatic proximity, concentration of information, order of the terms, words weight...
NQL use a new proprietary technique to create a sequential index which give you these advantages:
The Naturel Query Language makes it easy for users
Our sorting methods (using 5 relevance factors) delivers a very precise answer and saves a lot of time and system resources.
The indexing process isn't affected in a significant way by the size of the database (in the long run,
NQL will be much faster than competitive products).
The database Update is incremental (so, the updating process is very fast!).
NQL allows multiple users to access the indexes at the same time, without affecting, the speed of the search.
The search is not only easy and precise, it is also very fast.
This new technology is very easy to integrate.
THE NATUREL QUERY LANGUAGE
How does Naturel handle multi-word searches in comparison with traditional products?
Naturel is radically different from traditional text search products. Naturel does not implicitly add "and," "or," or proximity operators between words. The technology developed by our R&D team studies the "closest proximity" first, then the "and" values and finally the "or" values. Naturel does the work instead of asking the user to do it. Naturel also applies other statistical criteria to increase the accuracy of results before displaying them. Naturel's cutting edge technology lets users formulate queries in natural language.
After performing a statistical analysis of the results, Naturel displays the information based on its relevance.
AGIR's unique technology makes locating information easier and corrects a number of
imprecision inherent in Boolean logic.
Results are sorted according to the following statistical criteria:
Presence
If all words in a query are present in a part of the text, that part is automatically considered to be more relevant than sections where some of the words are missing.
Proximity
Naturel searches through a document, finds words in the proper sequence and then calculates the words' proximity. The closer the words are to each other, the greater the importance assigned to the document that contains them.
Concentration
When looking for a particular word, expression or sentence, Naturel assigns greater importance to texts whose main subject relates to the information the user is looking for.
Order
A text that contains words in exactly the same order as in the query is considered more relevant than texts that contain the words in a different order.
Weight
Naturel weights words according to the number of times they appear in the database. Words that occur often are considered less important than those that appear less frequently.
For example:
If the user is looking for Article 409 in a legal text, Naturel presents the document that has the most information on 409 before it presents documents that contain many instances of the word article. Why? Because 409 appears less often in the database than article does, Naturel gives more weight to 409. In fact, a word that occurs many times in a database loses importance, as do stop words.
Here is an example of how Naturel differs from traditional technology
Query: The user is looking for a candidate who is fluent in English, French and Chinese. The candidate should have experience in international politics and an educational background in law, finance and marketing. A knowledge of computers is also required.
Note: The perfect candidate may prove hard to find!
Traditional technology:
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The first attempt:
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"English & French & Chinese & International & Law & Finance & Marketing & Computers."
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Result: The query is too restrictive and would not yield a
result
The second attempt:
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"English or French or Chinese or Politics or International or Law or Finance or Marketing or Computers".
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Result: The query would most likely present all the candidates in the database.
If you were looking for the best candidate, what would you do? Without extensive knowledge of the text retrieval system, it would be very difficult to narrow the search using queries like these.
Naturel technology:
The query can be expressed in natural language.
| "Candidate who speaks English, French, Chinese, has experience in international politics, law, finance and marketing, and is computer literate."
|
Using this algorithm, Naturel will find that no document matches the criteria perfectly, but that three documents may be of interest.
The first candidate satisfies most of the criteria, but does not speak Chinese or have any marketing experience.
The second person speaks all three languages, but does not have experience in law or in international politics and is not computer literate.
The third candidate speaks English and has experience in law.
The documents are presented in the order of their relevance. A given document is always more relevant than the document that follows it.
The Boolean operators normally used in traditional products are also available in
Naturel.
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