Text Mining

Definition :Text mining and text analytics are broadumbrella terms describing a range of technologies foranalyzing and processing semi-structured andunstructured text data. The need is to turn text intonumbers so powerful algorithms can be applied tolarge document databases.

Text Mining areas with related field

We can broadly classify text mining techniques based on the relation with various field.

TM Classification

Search & IR (Information Retrieval)

Concept Extraction

Information Extraction

Document Clustering

Document Classification

Web mining

NLP ~ Computational linguistic

Topics

Inverted Index (IR) Feature Selection (classification) Link analytics (web mining) Sentiment Analysis (classification) Name Entity Extraction(information extraction) Part of speech tagging(nlp) Synonym identification (content extraction) Topic modeling (content extraction) Question answering(nlp) Document clustering & classification(clustering) Spam filtering (content extraction)

Examples

Use of text mining to reveal trends

Sentiment analysis using customer reviews

Defense against spam mails.

Genre detection based on a training set from music site(uses classification)

Market basket analysis- associating commonly found terms together

Classical example of watson (NLP)

Use of topic modelling in R to show the probabilistic modeling of term frequency occurrences in documents.

Performing ontology on news article (multi-faceted topic hierarchies for easier searching and browsing)