Sentiment Analysis to Build a Model Driven Decision Support System for a Complex Service Enterprise...

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Sentiment Analysis to build a Model Driven Decision Support System for a Complex Service Enterprise Rachit Sood Arati Mahimane CSE 788 Enterprise Architecture Spring 2012

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Transcript of Sentiment Analysis to Build a Model Driven Decision Support System for a Complex Service Enterprise...

Page 1: Sentiment Analysis to Build a Model Driven Decision Support System for a Complex Service Enterprise (1)

Sentiment Analysis to build a

Model Driven Decision Support System for a

Complex Service Enterprise

- Rachit Sood- Arati Mahimane

CSE 788 Enterprise Architecture

Spring 2012

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CSE 788 Enterprise Architecture 2

Goal

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•Perform sentiment analysis on raw data obtained from feedback provided on various services provided by an enterprise – City of Columbus.

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•Identify and model a number of abstract sentiment visualization layers over the components of the enterprise.

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CSE 788 Enterprise Architecture 3

Value

Supports decision making for service improvements for the enterprise.

Provides review at multiple granularity levels which helps in identifying the gaps and redundancies in the enterprise.

By gauging the relative business value of different areas, it is easy to identify components which demand immediate attention.

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CSE 788 Enterprise Architecture 4

Service InnovationExtracting meaningful information and

its context by using ‘Sentiment Analysis of Letters to the Editor’.

Extends the concept of component business modeling to support decision making based on continuous feedback.

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Next Steps

Develop an ontology from the input data set and standard dictionaries.

Use the ontology to effectively classify input data.

The classification will be done at a series of levels with highest accuracy at the lowest level.

The lowest level would map to a service and would provide an accurate feedback of its operations.

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CSE 788 Enterprise Architecture 6

Data and ModelData required: Letters to the Editor of

‘Columbus Dispatch’This data will be analyzed using

Apache Lucene which is a high-performance, full-featured text search engine Java library.

Model: Component Business Model (CBM). The CBM framework is already being used to develop a component view of the enterprise.

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Three phases of the CBM analysis:

•Sentiment analysis will yield a "heat map" which highlights the components that represent the greatest user satisfaction.

•It will also help to identify the components which need improvement.

1. Insight Phase

•Overlay the heat map onto the existing business to identify gaps between "to-be" vision and the "as-is" view.

2. Architecture

phase

•Decide on how to close the gaps.

•Decide the areas to be focused, how much change can be done.

3. Investment phase