Anawis 2014 (†525)Anawis, Mark A. "Text Mining: The Next Data Frontier." Scientific Computing (6 January 2014).
- text mining : Text mining can be defined as the analysis of semi-structured or unstructured text data. The goal is to turn text information into numbers so that data mining algorithms can be applied. It arose from the related fields of data mining, artificial intelligence, statistics, databases, library science, and linguistics. ¶ There are seven specialties within text mining that have different objectives. These can be decided by answers to the questions shown in the decision tree in Figure 2. These specialties are: 1. Information retrieval: storage and retrieval of documents 2. Document Clustering: group and categorize documents using data mining clustering algorithms 3. Document Classification: group and categorize documents based on labeled examples 4. Web mining: understand relationships of hyper linkages of documents on the web 5. Information Extraction: identify specific facts and relationships of unstructured text 6. Natural language processing: understanding language structure, such as parts of speech 7. Concept extraction: group words into similar semantic groups (†834)