PROJECT TOPICS ON DATA MINING

 

 

 

PROJECT TOPICS ON DATA MINING

    Project Topics on Data Mining can be more precisely called as a hub of unique and novel ideas for data mining projects. Our Project Topics on Data Mining has started with an initiative of top experts from the world who wants to share their valuable information to the budding students to make their career sounding. Along with best and unique ideas for your project, we provide complete support for your project which includes complete documentation/thesis, presentation, journal publications and conference support. This is the reason why majority of scholars prefer us, as our guidance offers an all round support. Our standard and work quality has made us world’s no. 1 institute for research guidance and support. Give your hands to us; we will give our supportive hands to make your research a ground breaking success.

PROJECT TOPICS ON DATA MINING

    Project Topics on Data Mining gives you an ease to select your project with your passion and Interest. Data Mining is actually an analysis practice to identify the patterns and regularities available in the large set of data. Scholars can prefer this domain due to its interdisciplinary nature and wide application. We never stick on static topics and existing issues, as it won’t give you the success, which you desire. Every student has their own individuality, which has to be focused to bring out the best in them. We have a dynamic environment where our versatile developers and experts mingle together to provide a research platform for the budding students to make their life colorful. We have provided below, a short and compact description about data mining concepts, which will guide you to choose your project topic.

HIGHLIGHTS ABOUT DATA MINING:

Features of Data Mining system:

  • Process large quantities of data
  • Incomplete and imprecise data
  • Complex data structure
  • Conventional statistical approach cannot be used
  • Heterogeneous data storage in legacy systems.
  • Analyzed using automated techniques

Steps followed in data Mining with knowledge discovery process:

  • Data cleaning[Removal of noisy and inconsistent data]
  • Data Integration[Combination of multiple data sources]
  • Data Selection[Analysis of relevant data]
  • Data Transformation[Consolidation and transformation of data]
  • Data Mining[Use of intelligent methods to extract pattern]
  • Pattern evaluation[Pattern identification]

Major Issue involved:

  • Handling incomplete data
  • Mining information from large databases
  • Handling of complex and relational data types
  • Efficiency and scalability of data mining algorithms
  • Heterogeneous database-data mining techniques

Software’s and Tools Used:

  • GATE[Natural Language processing and language engineering tool]
  • Carrot2[Clustering framework for text and search result]
  • ELKI[Advanced clustering analysis method written in Java]
  • KNIME[Konstanz Information Miner- comprehensive data analytics framework]
  • ML-Flex[Software package to integrate with third party machine learning package]
  • MLPACK Library[Machine learning algorithms in C++ Language]
  • NLTK[Natural Language Toolkit]
  • OpenNN[Open neural networks library]
  • Massive Online Analysis[Real time big data stream mining concept]
  • Orange[Component based data mining and machine learning software]
  • R Programming[Programming language for statistical computing, graphics and data mining]
  • Scikit learn[Open source machine learning library]
  • SCaViS[Java cross platform data analysis framework]
  • Torch[Open source deep learning library]
  • SenticNet API[For opinion mining and sentiment analysis]
  • UIMA[Unstructured Information Management Architecture]
  • RapidMiner[Used for machine learning and data mining]
  • Weka[Suite of machine learning software applications]
  • Oracle Data Mining
  • NetOwl[for Multilingual text and entity analytics]

 Major Applications of Data Mining:

  • Web mining and web content analysis
  • Weather prediction and climate change studies
  • Social Data mining
  • Mining customer behavior in Retail shop
  • Crime or fraud detection
  • Implementation of Enterprise Resource planning
  • Text Mining
  • Knowledge extraction using decision tree
  • Data leakage detection in cloud
  • Movie rating prediction
  • Social media mining
  • For commercial purpose and Market basket analysis using Apriori algorithm
  • Security in Web mining framework
  • Used in finance and banking, Tax governing, manufacturing and marketing.
  • Used for security enhancement using algorithms like

                        Botnet detection

                        Deep packet inspection

                        Web attack detection

                        Web proxy log analysis

                       Algorithmic alert correlation

                       Host based threat detection

                       Intrusion detection and network profiling

Recent Research topics in Data Mining:

  • The process of a Proactive Small Cell Interference Mitigation Strategy for Improving Spectral Efficiency of LTE Networks in the Unlicensed Spectrum based on usICIC
  • A new technique Secure and Robust Multi-Constrained QoS Aware Routing Algorithm for VANETs
  • The new process of the distance-assisted used for the research and optimization of AD-Hoc network localization algorithm
  • An efficient usage of MANET for remote pastoral areas of Tibet to perform Integrated wireless communication system
  • An efficient mechanism distributed mobile cloud computing model for secure big data
  •  A User Experience Oriented Middleware for Mobile Cloud Computing based on Context Aware Mobile Cloud Services

   Using our Project topics on Data mining, you can explore the field of research due to it’s the novelty and originality it reflects. You can clear your doubts further by having a session with our top experts, who are the best source of research guidance.

 

 

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