sql - How to get almost matching string from Oracle table? -


i have table in oracle 4 columns. table data in oracle.

now user can enter input string "operation knee right" (which valid) query , query should return icd code (ikr123) matches of word in diagnosisname column.

following current query.(not giving proper output)

select diagnosisname   (select diagnosisname,     utl_match.jaro_winkler_similarity('%operation knee right%',diagnosisname)   icd_code   order utl_match.edit_distance_similarity('%operation knee right%',diagnosisname) desc   ) rownum<2;

this query giving me output "left knee operation" expectation "right knee operation".

there few things note usage of utl_match:

  • edit_distance_similarity : returns integer between 0 , 100, 0 indicates no similarity @ , 100 indicates perfect match.
  • jaro_winkler_similarity : returns integer between 0 , 100, 0 indicates no similarity @ , 100 indicates perfect match tries take account possible data entry errors.

order utl_match.edit_distance_similarity('%operation knee right%',diagnosisname) desc

this not going give correct result. since, considering possible similarity, however, not considering data entry errors. so, must use jaro_winkler_similarity.

operation knee right

you need keep in mind case of input , column values compare. must in similar case correct match. passing input in lowercase, however, column values in initcap. better convert both column values , input similar case.

let's @ below demonstration understand:

sql> data as(   2  select 'heart operation' diagnosis_name, 'ih123' icd_code dual union   3  select 'knee operation' diagnosis_name, 'ik123' icd_code dual union   4  select 'left knee operation' diagnosis_name, 'ikl123' icd_code dual union   5  select 'right knee operation' diagnosis_name, 'ikr123' icd_code dual union   6  select 'fever' diagnosis_name, 'if123' icd_code dual   7  )   8  select t.*,   9    utl_match.edit_distance_similarity(upper(diagnosis_name),upper('operation knee right')) eds,  10    utl_match.jaro_winkler_similarity (upper(diagnosis_name),upper('operation knee right')) jws  11  data t  12  order jws desc  13  /  diagnosis_name       icd_co        eds        jws -------------------- ------ ---------- ---------- right knee operation ikr123         20         72 knee operation       ik123          20         70 heart operation      ih123          25         68 left knee operation  ikl123         25         64 fever                if123          15         47  sql>

so, see how both different each other. jaro_winkler_similarity better job in identifying data entry errors , giving most close match. based on that, choose first row after sorting in descending order:

sql> data as(   2  select 'heart operation' diagnosis_name, 'ih123' icd_code dual union   3  select 'knee operation' diagnosis_name, 'ik123' icd_code dual union   4  select 'left knee operation' diagnosis_name, 'ikl123' icd_code dual union   5  select 'right knee operation' diagnosis_name, 'ikr123' icd_code dual union   6  select 'fever' diagnosis_name, 'if123' icd_code dual   7  )   8  select diagnosis_name   9   10    (select t.*,  11      utl_match.edit_distance_similarity(upper(diagnosis_name),upper('operation knee right')) eds,  12      utl_match.jaro_winkler_similarity (upper(diagnosis_name),upper('operation knee right')) jws  13    data t  14    order jws desc  15    )  16  rownum = 1  17  /  diagnosis_name -------------------- right knee operation  sql>

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