See here www.merriampark.com/ld.htm for information about the algorithm. This page has a link (http://www.merriampark.com/ldtsql.htm) to a T-SQL implementation by Joseph Gama: unfortunately, that function doesn't work. There is a debugged version in the also-referenced package of TSQL functions (http://www.planet-source-code.com/vb/scripts/ShowCode.asp?txtCodeId=502&lngWId=5), but this still has the fundamental problem that it only works on pairs of strings up to 49 characters.
CREATE FUNCTION edit_distance(@s1 nvarchar(3999), @s2 nvarchar(3999))
DECLARE @s1_len int, @s2_len int, @i int, @j int, @s1_char nchar, @c int, @c_temp int,
@cv0 varbinary(8000), @cv1 varbinary(8000)
SELECT @s1_len = LEN(@s1), @s2_len = LEN(@s2), @cv1 = 0x0000, @j = 1, @i = 1, @c = 0
WHILE @j <= @s2_len
SELECT @cv1 = @cv1 + CAST(@j AS binary(2)), @j = @j + 1
WHILE @i <= @s1_len
SELECT @s1_char = SUBSTRING(@s1, @i, 1), @c = @i, @cv0 = CAST(@i AS binary(2)), @j = 1
WHILE @j <= @s2_len
SET @c = @c + 1
SET @c_temp = CAST(SUBSTRING(@cv1, @j+@j-1, 2) AS int) +
CASE WHEN @s1_char = SUBSTRING(@s2, @j, 1) THEN 0 ELSE 1 END
IF @c > @c_temp SET @c = @c_temp
SET @c_temp = CAST(SUBSTRING(@cv1, @j+@j+1, 2) AS int)+1
IF @c > @c_temp SET @c = @c_temp
SELECT @cv0 = @cv0 + CAST(@c AS binary(2)), @j = @j + 1
SELECT @cv1 = @cv0, @i = @i + 1
Hi, please, it is possible to know the edit distance used in the fuzzy lookup/grouping. On this forum I read fuzzy lookup use 4-gram with fix size. Does exist any document explaining how fuzzy lookup calculate the similarity? In other word, what kind of edit distance, algorithm is used by fuzzy lookup/grouping? I hope I was enough clear with my poor english. Thanks All
Hi How do I get a nearest distance of a point? For example, I have two tables A and B and I want to find the nearest distance between the records of the two tables. In addition, one of the tables should also give me the distance. The data I have geo spatial data. Can this be done in SQL Help will be appreciated
Is there a recommended practice for mirroring in regards to distance? Is it best practice to mirror with both nodes at the same physical location and use another method for failing over to a remote location or can one just put the other node in the mirror a few thousand miles away? I'm suspecting not.
I'm trying to run a dyncamic query that returns all records within a specific distance of a certain point. The longitude and latitude of each record is stored in the database. The query is constructed from two dynamic variables $StartLatitude and $StartLongitude with represent the starting point.
I'm looking to find out how I'd go about setting up a database where avisitor to my site could punch in their postal code, and find out how farthey are from another postal code. For example, AutoTrader has this featureI believe to tell you how far the vehicle is from you. Dating sites havethem so you can do proximity searches.Anyone have any ideas where I could start? I'm thinking the post office,but if anyone else has suggestions, I'm open to hear them.Thanks!
I am new to data mining so please excuse my ignorance. Lets assume
- i have created a cluser model
- identified 3 clusters ( a, b, c)
- each record consists of 15 columns
- collecting new records( 15 variables) real time
what i would like to do is plot these new records programmatically as i collect them realtime. I assume this new record will belong to one of these three clusters. I believe we can find the cluster this new record belongs to by ' SELECT Cluster()....' and distance from the center of the cluster by ClusterDistance(). To plot this on a 2-dimentional space i need (x, y).
I am trying to use the haversine function to find the distance betweentwo points on a sphere, specifically two zip codes in my database. I'mneither horribly familiar with SQL syntax nor math equations :), so Iwas hoping I could get some help. Below is what I'm using and it is,as best as I can figure, the correct formula. It is not however,giving me correct results. Some are close, others don't seem right atall. Any ideas?SET @lat1 = RADIANS(@lat1)SET @log1 = RADIANS(@log1)SET @lat2 = RADIANS(@lat2)SET @log2 = RADIANS(@log2)SET @Dlat = ABS(@lat2 - @lat1)SET @Dlog = ABS(@log2 - @log1)SET @R = 3956 /*Approximate radius of earth in miles*/SET @A = SQUARE(SIN(@Dlat/2)) + COS(@lat1) * COS(@lat2) *SQUARE(SIN(@Dlog/2))SET @C = 2 * ATN2(SQRT(@A), SQRT(1 - @A))/*SET @C = 2 * ASIN(min(SQRT(@A))) Alternative calculation*/SET @distance = @R * @Cthnx,cjrsumner
I need to be able to take the latitude and logitude of two locations and compare then to determine the number of miles between each point. It doesn't need to account for elevation, but assumes a flat plane with lat and long.
Does anyone have any algorithms in T-SQL to do this?
Hi All, Does anyone have a Stored Procedure that works perfectly to retrieve all zipcodes within a specified zipcode and distance radius - a zipcode and radius is passed and the Store Procedure result shows all zipcodes that falls within that range.
I've got a working query which returns all leads within a supplied proximity to a city. I followed a tutorial I googled a couple months ago (can't find it now). It works, but would love others to look the query over (provided DDL and sample data) and tell me if it's as it should be.
Two things I don't like about query:
1. I have to do a UNION to another query that retrieves everything that is in the same city in order to have complete results. 2. very slow to retrieve results (> 1 minute)
I am new to DM and I am not sure which algorithm would be best to use.
I am trying to build a custom comparitor application that companies can use to compare themselves against other companies based on certain pieces of information. I need to group a company with 11 other companies based on 6 attributes. I need the ability to apply weightings to each of the 6 attributes and have those taken into consideration when determining which 10 other companies each company is grouped with. Each group must contain 11 members, the company for the user logged in and 10 other companies that it will be compared against.
At first I thought that clustering would be a good fit for this but I can not see a way to mandate that each cluster contain exactly 11 members, I cannot see a way to weight the inputs, and I think each company can only be in one cluster at a time which do not meet my requirements.
Well, i have read in claude seidman book about data mining that some algorithm inside in microsoft decision tree are CART, CHAID and C45 algorithm. could anyone explain to me about the tree algorithm and please explain to me how the tree algorithm used together in one case?
Hello,Do you know if the algorithm for the BINARY_CHECKSUM function in documentedsomewhere?I would like to use it to avoid returning some string fields from theserver.By returning only the checksum I could lookup the string in a hashtable andI think this could make the code more efficient on slow connections.Thanks in advanced and kind regards,Orly Junior
What kind of algorithm does the MAX command uses? I have a table that I need to get the last value of the Transaction ID and increment it by 1, so I can use it as the next TransID everytime I insert a new record into the table. I use the MAX command to obtain the last TransID in the table in this process. However, someone suggested that there is a problem with this, since if there are multiple users trying to insert a record into the same table, and processing is slow, they might essentially come up with the same next TransID. He came up with the idea of having a separate table that contains only the TransID and using this table to determine the next TransID. Will this really make a difference as far as processing speed is concerned or using a MAX command on the same table to come up with the next TransID enough? Do you have a better suggestion?
I have few questions regarding Clustering algorithm.
If I process the clustering model with Ks (K is number of clusters) from 2 to n how to find a measure of variation and loss of information in each model (any kind of measure)? (Purpose would be decision which K to take.)
Which clustering method is better to use when segmenting data K-means or EM?
I want to predict which product can be sold together , Pl help me out which algorithm is best either association, cluster or decision and pl let me know how to use case table and nested table my table structure is
hi, i am using sqlserver2005 as back end for my project. actually we developing an stand alone web application for client, so we need to host this application in his server. he is not willing to install sql server 2005 edition in his sever so we r going by placing .mdf file in data directory of project.
but before i developed in server2005 i used aes_256 algorithm to encrypt n decrypt the pwd column by using symmetric keys.it is working fine.
but when i took the .mdf file of project n add into my project it is throwing error at creation of symmetric key that "Either no algorithm has been specified or the bitlength and the algorithm specified for the key are not available in this installation of Windows."