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A presentation by W H Inmon ANALYZING CALL CENTER TEXT.

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Presentation on theme: "A presentation by W H Inmon ANALYZING CALL CENTER TEXT."— Presentation transcript:

1 A presentation by W H Inmon ANALYZING CALL CENTER TEXT

2 Lots of companies have call centers

3 But do you know what is being said? Can you examine 100% of your call center conversations? What is going on in your call centers? What is on our customers mind?

4 When you ask a company about their call center, what do they tell you? - how many calls a day they get - how long their calls are And that is all they know.

5 Descriptive conversation text

6 textual ETL unstructured data taxonomy relational data base With Textual ETL and visualization now you can easily and quickly capture and analyze ALL your call center conversations Now you can know what your customers are actually saying

7 textual ETL unstructured data taxonomy relational data base And once you have created a relational data base with Textual ETL, you can do your analysis with visualization visualization

8 A dashboard showing what is going on in the call center

9 textual ETL unstructured data taxonomy relational data base Once you have created your data base, you can analyze it in any way you want Statistical Analysis visualization

10 textual ETL unstructured data taxonomy relational data base Building the relational data base -

11 Language is complex

12 So what do you need to do to text to turn it into a form that can be analyzed?

13 Proximity analysis inline contextualization Taxonomy/ontology resolution Custom variable formatting date standardization Not surprisingly, there are many facets to executing Textual disambiguation

14 …the Dallas cowboys always play on Thanksgiving….. Proximity analysis

15 …she drove her Honda past the telephone booth….. …he walked past the red Volkswagen in a hurry….. …the yellow Porsche ran well ahead of the traffic…… Car Honda Ford Volkswagen Porsche Toyota taxonomy …she drove her Honda/car past the telephone booth….. …he walked past the red Volkswagen/car in a hurry….. …the yellow Porsche/car ran well ahead of the traffic……

16 Whereas, John Quincy as tenant in common has purchased….. owner Beginning delimiterEnding delimiter Inline contextualization

17 …remove OL-995-AT from the exhaust manifold… …remove OL-995-at from the exhaust manifold… CC-999-cc Custom variable formatting

18 …on July 20, 1945 singer Kim Karnes came into this earth….. Date:19450720 Date standardization

19 A standard relational table

20 Doc namebyte value context

21

22 Content of text is the easy part Context of text is the hard part

23 And where is text found? EVERYWHERE!!! Medical records Call center Email Contracts Warranty Insurance claims Human resources Letters And many, many more places

24 + Textual ETL + visualization = Business Value For more information about Textual disambiguation, see – www.forestrimtech.com

25 Now you can unlock the text that is found in your corporation


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