Application of Data Mining Techniques to a Selected Business Organisation with Special Reference to Buying Behaviour

@article{Hilage2011ApplicationOD,
  title={Application of Data Mining Techniques to a Selected Business Organisation with Special Reference to Buying Behaviour},
  author={Tejaswini Hilage and R. V. Kulkarni},
  journal={ArXiv},
  year={2011},
  volume={abs/1112.4031}
}
Data mining is a new concept & an exploration and analysis of large data sets, in order to discover meaningful patterns and rules. Many organizations are now using the data mining techniques to find out meaningful patterns from the database. The present paper studies how data mining techniques can be apply to the large database. These data mining techniques give certain behavioral pattern from the database. The results which come after analysis of the database are useful for organization. This… 
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References

SHOWING 1-6 OF 6 REFERENCES

From data to knowledge mining

TLDR
A new data mining technique, called knowledge cohesion (KC), is presented, which takes into account a domain ontology and the user's interest in exploring certain data sets to extract knowledge, in the form of semantic nets, from large data sets.

On the Use of Optimization for Data Mining: Theoretical Interactions and eCRM Opportunities

TLDR
It is argued that the reformulation of eCRM problems within this new framework of analysis can result in more powerful analytical approaches.

Tree-based partitioning of date for association rule mining

TLDR
This paper describes a partitioning approach which organises the data into tree structures that can be processed independently and presents experimental results that show the method scales well for increasing dimensions of data and performs significantly better than alternatives, especially when dealing with dense data and low support thresholds.

Sapphire: experiences in scientific data mining

TLDR
The Sapphire system architecture that was motivated by the needs of a diverse set of applications is described and some of the challenges faced in analyzing data ranging from a megabyte to several terabytes are discussed.

Data mining of tuberculosis patient data using multiple correspondence analysis

TLDR
It is suggested that MCA could be a useful tool in informing commissioning of TB services and is a useful technique for displaying association of variable categories used in TB epidemiology.

Challenges and Opportunities in Mining Neuroscience Data

TLDR
The need for neuroinformatics approaches to accelerate progress is discussed, using several illustrative examples, and the need for cultural and infrastructure changes is underscored if neuro informatics is to fulfill its potential to advance the understanding of the brain.