Re: How to find double entries - Mailing list pgsql-sql
From | Jean-David Beyer |
---|---|
Subject | Re: How to find double entries |
Date | |
Msg-id | 480AA253.4070603@verizon.net Whole thread Raw |
In response to | How to find double entries (Andreas <maps.on@gmx.net>) |
List | pgsql-sql |
Andreas wrote: > Hi, > > how can I find double entries in varchar columns where the content is not > 100% identical because of a spelling error or the person considered it > "looked nicer" that way? > > I'd like to identify and then merge records of e.g. 'google', 'gogle', > 'guugle' Then I want to match abbrevations like 'A-Company Ltd.', 'a > company ltd.', 'A-Company Limited' > > Is there a way to do this? It would be OK just to list candidats up to be > manually checked afterwards. > > This is really tough, whether you use postgreSQL or not. I once worked for a large regulated monopoly who had to look up stuff in telephone books a lot. Several of us got a magnetic tape with all the business, professional, and government listings for a county on Long Island in it; we thought residential would be too easy and did not have the disk space for it (in those days, hard drives cost $40,000 and held 40 Megabytes). One of the things we did was do leading substring partial matching. I.e., we could look for "J Smith" and find "Smith, John Robert"; we could find him with "Rob Smit" as well. This helped because people did not put their names in the right order. Sometimes they said "Smith, John" and other times they said "John Smith" or "J Smith" and meant the same guy. Sometimes they said "White St" or "White Street" when they meant "White Road". And so it went. Sometimes they spelled her name "Jeannine" when she spelled it "Genine". So the question always ended up being what did they really mean. To make matters worse, someone had run a program over the data to spell out abbreviations, but that generated "42 Saint" instead of "42 Street" and problems like that. Also, if a field was too big, the data-entry clerks just kept on typing into the next field, so a lot of entries had, as an address, "If no entry call" I stuck in a phonetic matcher (similar to Soundex coding) so that a query for "Ristorante Italiano" would find "Mom's Pizza Italian Restaurant". It would also find Genine whey you were looking for Jeannine. People often got the towns wrong. Around here, there is a town on the map, but the telephone company had that in another town, and the tax collector had it in yet another town. So towns were weighted lower than names. For government listings, there was a separate record for each line in the telephone book, so you would get entries like this, each line a separate record: U S Government Federal Aviations Administration Kennedy Airport Pilot Information Arrivals Departures We had to make it find "Pilot Arrivals" so indexing was not trivial until you figured out how to do it. But when all was said and done, we put a program on the output that displayed answers in terms of decreasing goodness of match and stuck the users with deciding what they wanted. A big trick was to do all this without doing a sequential search of the database. -- .~. Jean-David Beyer Registered Linux User 85642. /V\ PGP-Key: 9A2FC99A Registered Machine 241939./()\ Shrewsbury, New Jersey http://counter.li.org^^-^^ 21:30:01 up 33 days, 2:32, 1 user, load average: 4.06, 4.07,4.11