Knowledge Engineering

We are entered in the age of Innovation Economy. An age of rapid and dramatic change, an age where innovative ideas create value. Innovation will be the prime source of prosperity, particularly in our modern industrialized countries.

Knowledge, ideas and needs are fueling the innovation. Society change and new products or services are creating new needs; society change and new goods are driven by the innovation; finally, knowledge and ideas are the main source of innovations. A lot of new ideas come from new discoveries, new knowledge in fact.

The KNOWLEDGE is the main pillar of the innovation. The sum of knowledge and the stream of information exceed the capacity of one human. The consequence is the knowledge is split in thousand of specialities that individual human being can handle. Each specialist has a deep knowledge of a small number of topics.

Today, any major innovations involve the deep knowledge and understanding in many fields. Only a few big companies can afford to have hundred of specialists, but it is not enough, the communication between them must be efficient and, of course, should not cost the main part of their time!

When I started to work as process engineer and lab manager, in a computer tape and floppy disks manufacturing company, quickly I understood that many scientific and technical fields where involved, such as: the magnetism, the rheology of polymers and dispersions, the cross-linking of polymers, the lubricants, the polymers degradation, the errors detection and correction algorithm, the applied statistics... , that was 23 years ago!

It is an obligation to manage the knowledge efficiently, if we want to continue to innovate. Only a machine can analyse, extract pertinent information, compare information, regroup information, archive and retrieve information coming from thousand of papers, publications, web sites and blogs.

The power of the personal computer, the omnipresence of internet incited me to write TexLeAn.

Today, TexLexAn is able to do some basic operations on a text document,
such as :

- Estimate the reading time and its difficulty.
- Evaluate the sentiments expressed (positive or negative sentiments).
- Extract the keywords.
- Categorize (or classify) the document.
- Summarize by extraction of the relevant sentences.
- Archive the document.
- Search in the archived summaries and retrieve documents.

In the future, TexLexAn will be able to:
- Regroup the documents (clusterization) per topics.
- Compare documents and extract similarities and divergences.
- Summarize a group of documents.