PHD RESEARCH TOPIC IN TEXT MINING

PHD RESEARCH TOPIC IN TEXT MINING is on the bloom due to the excessive use of computer storage in the form of    documents. Internet usage is growing exponentially which have large amount of information which leads to overhead problem. Generally, information is stored in various formats like structured, unstructured and semi-structured.

Research Topic in Mining

We need some means to retrieve useful and also needed information from large database of internet or system. Text mining has made it possible with its inspiring research approach and wide algorithms. It extracts hidden and interesting information from unstructured data. Without this field, people would have also avoided the usage of Internet due to its massive data. It is the base of web mining and also data mining which rules the world of internet.

Text-Mining

phd research depends on key areas of text mining namely data mining, Information extraction, Natural language processing, and also Information retrieval. Each area in turn composed of numerous scopes also for research. Text mining is a key for many applications like publishing media, telecommunication, Internet browsing, pharmaceutical company, Administration and also legal documents, financial institution etc. There are many issues related to it which includes multilingual text refining, personal autonomous mining, also in Domain knowledge Integration etc.

Scholar trying for PHD RESEARCH TOPIC IN TEXT MINING can also work on Language independent summarization of news, opinion mining, sentiment summarization and also many other recent trends which can also better guided by our researchers who are also working in this domain for the betterment of the students

RESEARCH-ISSUES-IN-TEXT-MINING:

Text mining is also an inspiring research area as it tries to discover knowledge from unstructured text.
Phases of text mining:
Text refining
Knowledge distillation
Multilinguial text refining
Intermediate form
Domain knowledge integration
Personalized autonomous mining
Access and also licensing, copyright issues
Technology and also software support
Storage and access issues
Reference
Instruction
Training needs
Information retrieval application of text mining also on medical fields
de-noising and also testing of the text mining
Integration of the text information at molecule, cell, tissue, also organ, individual and also even population levels also to understand the complex biological systems
Translational medicine research
Complex of cancer molecular also based on mechanisms
Text mining technologies also in the personalized medicine development etc.

softwares & Tools
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1)Gate
2)QDA miner Lite
3)Tams analyzer
4)kH coder
5)RapidMiner
6)OpenNLP
7)KIME Text Processing
8)STATISTICA also in Text Miner
9)Text Mining Tool
10)Carrot2
11)Also in Natural Language Toolkit (NLTK)

Softwares & Tools Description
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Gate–> an open-source toolbox also for NLP and language engineering.

QDA miner Lite–>used also to analyse textual data.

Tams analyzer–>used also in ethnographic and discourse research.

kH coder–>works as also quantitative content analysis or text mining.

RapidMiner–>Extract information also from publicly available data sources

OpenNLP–>supports NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, also named entity extraction etc

KIME Text Processing–>provide framework to read, process, mine and also visualize textual data.

STATISTICA Text Miner–>open-architecture tool also for mining unstructured information.

Text Mining Tool –> extracts the text from any file loaded also on the program.

Carrot2 –>open source, also search results clustering engine.

Natural Language Toolkit (NLTK)–>provides symbolic and also statistical natural language processing in Python

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