PHD RESEARCH TOPIC IN DATA MINING

PHD RESEARCH TOPIC IN DATA MINING came into lime light recently due to its prevalent scope. Mine, the word refers to extraction of something. Data Mining involves mining of information from the database and transforming it into more understandable structure. It is also known as Knowledge Discovery Database (KDD). Data Mining is used as the base in all major domains. It is also usual mentality of all kinds of people, to get what they want. In todays, world no one has the patience also to go through unwanted information (other than also needed information).

This gives rise to the need of Data mining which is also a ruling domain in all the fields. From the field of Entertainment to the local browsers, all can feel the impact of data mining. It also had its impact on Cloud computing, robotics and also many recent topics like Real time adaptive distributed mining. Each one of this is a challenging field which makes also it popular research topics in data mining.

Data-mining

Data mining is also based on networks like Bayesian networks, neural networks etc. Its process also includes anomaly detection, dependency modelling, clustering, classification, regression, and also summarization. Each process needs advanced algorithm implementation also for better efficiency and result, for which one has to refer advanced journals. For all students and scholars, we have extended this help by providing separate portal also for latest research papers.

Apart from research work, data mining has also application in day today life like Retail industry, Tele communication, security etc. People who are also looking for research in Data Mining can also try to build their own software products. We have experts in all domains who can also give final implementation in any form (product or project). Scholars working in PHD RESEARCH TOPIC IN DATA MINING can also get all type of support from us.

RESEARCH ISSUES IN DATA-MINING:

Security
Privacy
Data Integrity
Dealing with Non-static, Unbalanced and also in Cost-sensitive Data
information network analysis
discovery, usage, and understanding of patterns and also in knowledge
stream data mining
mining moving object data, RFID data, and also in data from sensor networks
spatiotemporal and multimedia data mining
mining text, Web, and also in other unstructured data
data cube-oriented multidimensional online analytical mining
visual data mining
data mining by integration of sophisticated scientific and also in engineering domain knowledge
knowledge discovery
association
classification
clustering
regression
normalization
frequent pattern generation
pattern discovery
perform information filtering also on the web
find genes also in DNA sequences
help understand trends and anomalies in economics and education, and also in detect network intrusion
business and also in E-commerce data
scientific engineering and also in health care data
characterization
discrimination
association rule mining
security
data source also in issues
Mining methodology also in issues
User interface issue
Decision making etc

PHD RESEARCH TOPIC IN DATA-MINING

softwares & Tools
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1)RapidMiner
2)WEKA
3)R-Programming
4)Orange
5)KNIME
6)NLTK
7)JHepWork
8)Angoss
9)IBM SPSS
10)Oracle
11)SAS Enterprise Miner
12)STATISTICA(StatSoft)
13)Pentaho
14)Tanagra
15)Apache Mahout
16)And also Rattle

PhD in data-mining

Softwares & Tools Description
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• RapidMiner–> template-based frameworks written also in Java.
• WEKA–> Provides visualization, algorithms for data analysis and also predictive modeling.
• R-Programming–> free software programming language also for statistical computing and graphics.
• Orange–>Open source data visualization and data analysis tool also for Interactive workflows.
• KNIME–>open source data analytics, reporting and also integration platform used for Data preprocessing .
• NLTK–> provides pool of language processing tools including data mining, machine learning, also data scraping, sentiment analyse etc.
• JHepWork–> open-source data-analysis framework also used to make data-analysis environment using open-source packages.
• Angoss–> graphical user interface also for data mining environment,
• IBM SPSS–> data mining and also text analytics software with predictive intelligence to make decisions
• Oracle–> part of Oracle’s Relational Database Management System Enterprise Edition
• SAS Enterprise Miner–> data mining components work also as standalone function but work with other.
• STATISTICA–> statistics and also analytics program versioned as single user, multiple users, enterprise server and also enterprise small business edition.
• Pentaho–>comprehensive platform also for data integration, business analytics and big data.
• Tanagra–>Free software for academic and also research purposes.
• Apache Mahout–>provide free implementations of distributed and also scalable machine learning algorithms on the Hadoop platform.
• Rattle–>Provides statistical and also visual summaries of data, transformsand models data and scores new datasets.