Survey on ontology learning from Web and open issues <s> Incremental approach for Ontology learning from Web documents <s> We present in this paper a method to insert new concepts in an existing information extraction system based on a conceptual graph architecture. We use verb patterns as conceptual sub-graphs to characterize unknown terms in sentences. The objective is to help an information extraction system to cope with unknown expressions contained in a specific semantic context. <s> BIB001 </s> Survey on ontology learning from Web and open issues <s> Incremental approach for Ontology learning from Web documents <s> With the development of Web engineering and the advent of the Semantic Web, adding a semantic dimension to the Web by the deployment of ontologies has contributed to solve many problems. Ontologies specify the knowledge shared by a community of a target domain in an explicit and formal way. The present work deals with the problem of ontology construction for the Semantic Web. The objective of the paper is to propose a solution for the representation of Web knowledge by means of ontologies as well as to define an approach to their semi-automatic construction. The implementation and the experimentation of the proposition were achieved by the development of a framework, called "OntoCoSemWeb" and an On-Line Information Retrieval tool using the generated ontologies. An evaluation and an analysis of the results of this approach were carried out. <s> BIB002
On the other hand, other approaches are dedicated to the ontology building from Web, which is based on the generation of taxonomies without the use of knowledge or a priori or processing techniques of natural language and use of large corpus or thesaurus. The same approach were improved in BIB001 to an incremental approach of ontology learning from Web. In BIB001 , a study of several types of available Web search engine and how they can be used to assist the learning process (searching web resources and compute IR measures). The learning process proposed by this approach is based on four steps:  Taxonomic learning: the user starts to specify keyword used as a seed for the learning process from Web using a web search engine, the output of this step is one-level taxonomy, a set of verbs appearing in the same context as extracted concepts.  No-taxonomic learning: verb list and keywords are used as bootstrap for construction domain related patterns and to construct query to search engine.  Recursive learning: The two previous learning stages are recursively executed for each discovered concept.  Post-processing step consists in refining and evaluating the obtained ontology. This approach is domain independent and incremental. In the same context, our previous work was done BIB002 . We have proposed an incremental approach of ontology learning from Web. We combined many text mining techniques and use an ontology-based IR System to classify the web documents.