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PhD Topics in Big Data

Opt for niche PhD topics derived by expert researchers in Big Data
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Big Data Topics

Many a large volume of data is collected, processed, and transmitted through modern technology. New approaches to the conversion of such data through various algorithms, tools, and strategies constitute the academic discipline of Big Data. It has made possible the ways by we can analyse and manage the large datasets; how it is created, used and applied to different fields such as life sciences or physics. The issues related to data analytics are creating a new field of expertise, that is, a doctoral program with advanced skills for data scientists.

Students of PhD in Big Data experiment using various technologies to develop algorithms and models by which the big data sets can be managed with sophistication. PhD in Big Data is a multidisciplinary research program which enables the students to perform little but essential tasks of statistician, analyst, and an engineer etc. It is evident that it is not an easy task to get pace up with a multidisciplinary research and the struggle begins from the topic selection. But the academic field and previous researches are likely to lead to a redefinition of the research topic. Having an eagle eye on Big Data and its applications can help you better identify your research topic and an influential research in the discipline. This is why, we have derived a few PhD topics in Big Data below:

  • MFCM-OMA based big data clustering in E – commerce
  • A stride towards Privacy preservation in E commerce with the aid of ElGamal Cryptosystem.
  • Collaborative filtering based recommendation for predicting the E-commerce service using clustering algorithm.
  • Behavioural Analysis of a Fuzzy Rule Based Classification System for Big Data Classification with Data Mapping and bagging approach in a MapReduce Scheme
  • Incorporating Apriori Algorithm with MapReduce approach to Remove Classification problems
  • Analysis on MapReduce Framework in Imbalanced Classification Systems using Fuzzy Based AdaBoost Algorithm
  • Designing an Effective Approach for Mining Big Data from Heterogeneous Data Streams Using Fuzzy Frequent Pattern Method
  • Optimizing Fault Detection for Big Data Analytics through Evolutionary Computation.
  • An efficient approach for detection of failure in big data analytics using clustering and classification technique
  • An efficient technique for improving classification problem using clustering approach.

These topics are suggested by our team of qualified research consultants. The team also offers significant help to the research students to focus on a topic which is both relevant to implement practically and addressing a gap, or a contradiction in the literature of the Big Data.

You can request us for a unique research topic by writing in to us at contact@thesisandcode.com.

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