Text Mining Seminar and PPT with pdf report: The term text mining is very usual these days and it simply means the breakdown of components to find out something. If a large amount of data is needed to analyze then the text mining is the necessary thing, the text mining has a lot of attention due to its excellent results and the avail of text mining is enhancing day by day. There are many new patterns and trends in associating the information that people can discover in the text mining.

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Text Mining Seminar and PPT with PDF Report

Text mining has its applications in spam filtering, monitoring the public opinion, customer services and also in the e-mail support. The text mining is also called as “text analytics” and is a way that has the unstructured data. This unstructured data is used by the computers. For example, an image is considered as a qualitative or unstructured data, if it is broken into the pixels.

Estimation is that 80% of the information is unstructured and in this the emails, newspapers, contents, research journals and much more are included. The text mining is nothing but the process; in this, the large amount of data or information is tested to produce new data or information. It has the group of instructions and it makes the links between the unconnected files and along with that, it furnishes visual maps.

History of Text Mining:

In the mid of 1980,’s the text mining was evolved but it was not well developed due to lack of sophisticated technology. Later the technology developed and along with it, the text mining was also developed.

Working in Text Mining:

The text mining has many processes or working methods and all these are combined to obtain the results that are nothing but the working of text mining. The stages involved in it are:

  • Information retrieval systems
  • Natural language processing
  • Information extraction
  • Data mining
  1. Information retrieval system: The initial step in text mining is to search the body of documents and this happens in the information retrieval systems.
  2. Natural language processing: The natural language processing permits the computer to perform grammatical testing of a sentence towards the text of a document or file.
  3. Information extraction: The information extracting involves in the operation of data structuring. Thus, data structuring is considered as its vital performance.
  4. Data mining: Well, coming to the data mining, the data mining finds or searches the patterns in huge data to find the new knowledge.

Tasks of Text Mining:

There are many tasks that are used in the text mining but coming to the vital tasks then there are only three important tasks that are used in the text mining. The three tasks are as follows:

  • Exploratory data analysis
  • Information extraction and
  • Text classification

Features of Text Mining:

The features of text mining play an important role in having the wide range of applications to the text mining. Some of the features of the text mining are as follows:

  • Access to the data or information
  • It possess the feature of feature extraction
  • It has the text processing capabilities

Applications of Text Mining:

The text mining has the wide range of applications and they are as follows:

  • Text mining is used in data mining and also in the competitive intelligence.
  • Text mining is used in national security.
  • It also has the application in the scientific discovery.
  • Sentiment analysis components or equipment avail the text mining techniques.
  • Text mining is also used in the security applications of the internet.
  • It is also used in the biomedical applications Pub Gene.
  • The software applications avail text mining
  • It is used in the online media to clarify the data or information.
  • Business and marketing also avail text mining.
  • Text mining is used in academic applications if the academic applications needed huge or large databases.
  • It is also used in records management.
  • The social media monitoring also utilizes the text mining.

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Resources of Text Mining:

The resources which are used in the advancement of the text mining systems are as follows:

  • Corpora
  • Terminologies
  • Biomedical text mining for Chinese
  • Bio Lexicon
  • Anatomy Resources
  • Evaluation
  1. Corpora: The corpora furnish various annotations of various sizes and various domains. Some of the machines learned text mining tools are as follows:
    • ACE meta-knowledge
    • Bio cause
    • GENIA
    • GENIA meta-knowledge
    • GREC
    • HLMERA
    • Metabolite and enzyme corpus
    • Pheno CHF
  2. Terminologies: Terminologies are the time- sensitive medical inventory and these are the group of the terms related to the medical field.
  3. Biomedical text mining for Chinese: These resources of text mining are developed at Nac Tem.
  4. Bio Lexicon: This is used to support text mining in a biomedical field.
  5. Anatomy resources: These are the group of equipment and lexicon resources.
  6. Evaluation: The text mining systems evaluations are done based on their performances.

Content of the Seminar and pdf report for Text Mining

  • Abstract
  • Introduction
  • What is Text Mining?
  • Text Mining Methods
  • Text Mining Tasks
  • Application
  • Trends
  • Process
  • Resources
  • Features
  • Text mining and Data mining
  • Value and Benefits
  • Approaches to Text Mining
  • Conclusion

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