Hi guys

I'm really hoping that this at all possible?

Basically, I have a vehicle database with over 150,000 records. I have a single field called "description" which has approx. 200 words in it. An example of a description can be seen here:

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Insurance Group 15, 2 Year Unlimited Mileage Ford Direct Warranty, 2 Year Roadside Assistance Package, Appearance Pack, DAB Radio/CD & Ford SYNC, One Owner, Full Service History, Quickclear Heated Windscreen, 17" Alloy Wheels, Privacy Glass, Remote Central Locking With Retractable Key, Electric Door Mirrors, Five Star Euro N-Cap Rating, Rear Parking Sensors, Power Assisted Steering (PAS), Anti Lock Braking System(ABS), Rear Child locks, Ford Easyfuel, Immobiliser, Dual Airbags, Front & Side Airbags, Isofix Brackets, Side Impact Protection, Adjustable Door Mirrors, Six Speed Gearbox, Air Conditioning, Adjustable Steering Column, Electric Front Windows, Height Adjustable Drivers seat, Multi Function Display, Outside Temperature Indicator, Rev Counter, Split Folding Rear Seats, Trip Computer, iPod/MP3 Connectivity, USB Functionality, Body Colour Door Handles, Body Coloured Rear Spoiler, Front Fog Lights, Metallic Paint, Rear Wash Wipe, Part Exchange Taken as Full Deposit, Photographs Of Actual Car, Physical Car Available Viewing Today
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What I need to do is search the entire SQL database table and compile a list of the most commonly used words or phrases (that appear within commas). So for example, if the word "Immobiliser" is used in more than 10 records, then I need to display this. If "Rev Counter" is used in more than 10 records then this would display also. However, if "Outside Temperature Indicator" is only displayed in two separate records then this is not displayed in my list.

What I need to do is basically create a list of the most commonly used words and phrases (between commas) that can be found in the description fields within my table.

I have no idea where to start. What is the easiest way to achieve this?

Any help would be fully appreciated

Best regards

Rod from the UK