Therefore, in this research, we proposes a practical text mining
methodology for the science and technology trend analysis, and conducts mining tasks such as making an ontology, topic analysis, and network relationship analysis.
The era of applying text mining
approaches to biology and biomedical fields came into existence in 1999.
Figure 2 defines CompleteText mining model to process the text mining
from selecting the targeted dataset to pattern discovery and interpretation of evaluated knowledge .Facts are stored in relational database  for the analysis.
Knowledge base utilized in  empowers huge quantity of machine learning methods for diverse number of text mining
There are seven specialties within text mining
that have different objectives.
* Text Mining
e ideal para inspecionar mudancas no mercado, ou para identificar ideias.
This requires expertise in areas such as text mining
, social network analytics and data science.
* knowledge extraction from text, text mining
combined with social network analysis.
CURRENT ANTI-FRAUD TECHNOLOGY Automated Red Flags 64% Scoring Capability 60% Link Analysis 57% Workflow Routing 43% Text Mining
40% Predictive Modeling 40% Geographic Data Maps 23% Data Source: Coalition Against Insurance Fraud.
The first attempts at text mining
of the biomedical literature date back to 1998.
However, these languages generally are not optimized for the purpose of text mining
. In other words, they usually consider queries as individuals and only return raw results for each query.
Since much of knowledge is in the form of unstructured information, a chapter on Text mining
could have been a useful addition.