NEC automates large-scale data prediction for
business systems
– Predictive Analytics Automation Technology
quickly and accurately analyses multiple databases –
Tokyo, December 15, 2016 –
NEC Corporation
(NEC; TSE: 6701) today announced the development of a “Predictive
Analytics Automation
Technology” that completely automates the process for large-scale data
predictive analytics performed by relational databases that are widely
used for business systems.
NEC Corporation
(NEC; TSE: 6701) today announced the development of a “Predictive
Analytics Automation
Technology” that completely automates the process for large-scale data
predictive analytics performed by relational databases that are widely
used for business systems.
Currently,
when analyzing relational databases composed of multiple databases, a
great deal of work is required for processes that include the discovery
and association
of complex relationships between databases by skilled scientists, as
well as the adjustment of prediction models by machine learning.
Moreover, there is a shortage of well-trained data scientists capable of
handling the rapidly growing need for advanced data
analysis. As a result, there is heavy demand for highly accurate
analysis methods that quickly perform large-scale data analysis and are
user friendly for non-experts.
when analyzing relational databases composed of multiple databases, a
great deal of work is required for processes that include the discovery
and association
of complex relationships between databases by skilled scientists, as
well as the adjustment of prediction models by machine learning.
Moreover, there is a shortage of well-trained data scientists capable of
handling the rapidly growing need for advanced data
analysis. As a result, there is heavy demand for highly accurate
analysis methods that quickly perform large-scale data analysis and are
user friendly for non-experts.
NEC’s
Predictive Analytics Automation Technology, developed as part of its
cutting-edge portfolio of artificial intelligence (AI) technologies, NEC
the WISE (*1),
automates the series of processes for predictive analysis, from the
extraction and design of a data item (feature that is effective for
analysis, to the creation of the most suitable predictive model. As a
result, even if an individual lacks advanced data
analysis skill, it is possible to perform predictive analysis in a
short time that is equal to or better than the accuracy of a
well-trained data scientist.
Predictive Analytics Automation Technology, developed as part of its
cutting-edge portfolio of artificial intelligence (AI) technologies, NEC
the WISE (*1),
automates the series of processes for predictive analysis, from the
extraction and design of a data item (feature that is effective for
analysis, to the creation of the most suitable predictive model. As a
result, even if an individual lacks advanced data
analysis skill, it is possible to perform predictive analysis in a
short time that is equal to or better than the accuracy of a
well-trained data scientist.
Joint
trials carried out by Sumitomo Mitsui Banking Corporation and NEC (*2)
confirmed that this technology successfully maintained accuracy and
reduced predictive
analysis to just one day, in comparison to conventional methods that
require 2-3 months of work by a professional analyst.
trials carried out by Sumitomo Mitsui Banking Corporation and NEC (*2)
confirmed that this technology successfully maintained accuracy and
reduced predictive
analysis to just one day, in comparison to conventional methods that
require 2-3 months of work by a professional analyst.
“This
new technology can contribute to the acceleration of business
decisions, including strategic planning, hypothesis verification and
policy implementation,
based on the discovery of new potential needs,” said Akio Yamada,
general manager, Data Science Research Laboratories, NEC Corporation.
“We aim to provide this technology as a service within the 2017 fiscal
year for companies seeking to independently perform
effective big data analysis.”
new technology can contribute to the acceleration of business
decisions, including strategic planning, hypothesis verification and
policy implementation,
based on the discovery of new potential needs,” said Akio Yamada,
general manager, Data Science Research Laboratories, NEC Corporation.
“We aim to provide this technology as a service within the 2017 fiscal
year for companies seeking to independently perform
effective big data analysis.”
Key features of this technology include the following:
1)
Strengthens NEC’s “Automatic Feature Design Technology” and automatically discovers feature quantities for relational data bases
Strengthens NEC’s “Automatic Feature Design Technology” and automatically discovers feature quantities for relational data bases
This
technology strengthens the “Automatic Feature Design Technology” that
NEC announced in 2015 and automatically designs the feature for the
relational databases that are widely used for business systems.
technology strengthens the “Automatic Feature Design Technology” that
NEC announced in 2015 and automatically designs the feature for the
relational databases that are widely used for business systems.
Based
on the relationship of multiple databases, AI searches for and
discovers hypotheses at high speed for combinations of data items
(feature
quantities) that are effective for prediction. Moreover, the system
automatically creates the large number of queries to generate features
from the databases.
on the relationship of multiple databases, AI searches for and
discovers hypotheses at high speed for combinations of data items
(feature
quantities) that are effective for prediction. Moreover, the system
automatically creates the large number of queries to generate features
from the databases.
As
a result, the time and labor for analysis is significantly shortened
since neither large amounts of work are necessary for feature hypothesis
planning, which is dependent on analysis experience and knowledge about
data, nor are database operations required for creating feature
quantities. Furthermore, in comparison to manual analysis, a great deal
more hypothesis searching can be executed in a short
time, more accurate analysis results can be achieved, and new findings
that may not have been noticed by manual processes may be discovered.
a result, the time and labor for analysis is significantly shortened
since neither large amounts of work are necessary for feature hypothesis
planning, which is dependent on analysis experience and knowledge about
data, nor are database operations required for creating feature
quantities. Furthermore, in comparison to manual analysis, a great deal
more hypothesis searching can be executed in a short
time, more accurate analysis results can be achieved, and new findings
that may not have been noticed by manual processes may be discovered.
2)
The “Automatic Prediction Model Design Technology” enables the automatic design of the most suitable model for the data.
The “Automatic Prediction Model Design Technology” enables the automatic design of the most suitable model for the data.
Based
on feature data, a wide range of prediction models are created using
various machine learning methods, such as NEC’s “Heterogeneous Mixed
Learning,” logistic regression and decision trees. The prediction model
that provides the most suitable analysis results for a user’s goals is
selected. Reasons for the predicted value calculated by the prediction
model are also provided.
on feature data, a wide range of prediction models are created using
various machine learning methods, such as NEC’s “Heterogeneous Mixed
Learning,” logistic regression and decision trees. The prediction model
that provides the most suitable analysis results for a user’s goals is
selected. Reasons for the predicted value calculated by the prediction
model are also provided.
Since
users are able to understand the basis of the prediction, they are also
able to make the most suitable judgement and implement the most
appropriate plan in response to a situation.
users are able to understand the basis of the prediction, they are also
able to make the most suitable judgement and implement the most
appropriate plan in response to a situation.
NEC
also developed a Graphic User Interface (GUI) for intuitive operation,
where a display provides users with easy to understand instructions to
search for feature
quantities and create predictive models.
also developed a Graphic User Interface (GUI) for intuitive operation,
where a display provides users with easy to understand instructions to
search for feature
quantities and create predictive models.
***
Note:
*1)
July 19, 2016 NEC announces new AI technology brand, “NEC the WISE”
NEC’s AI (Artificial Intelligence) Research
http://www.nec.com/en/global/rd/crl/ai/index.html
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