JDI: Text and MeSH

• Description:

  Read in text and MeSH and then perform JD indexing based on

  • word frequency count
  • document count for word
  
  text, MH, and SH are separated by '|'.

• Inputs:
  • a text and MeSH: text, MH, and SH are separated by '|'
  • a file, such as 9801.2004.TIABMH.in

• Algorithm:
  • Pre-Process (Input Filter):
    • Separate phrase and MeSH

    • Tokenize all words of the input phrase
    • Apply Word Extraction Filter (if it is MEDLINE TI or AB)
    • Apply acronym filter (TBD)
    • Filter out not legal words
    • Filter out duplicated words if unique flag is true
    • Assign the final words for processing

    • Tokenize SH and MH from the input Meshs
    • Filter out illegal Meshs (not in Mh-Jd Table or Sh-Jd Table
    • Assign legal Meshs
  • Process:
    • Get JD scores for each (legal) word in the text from DB: WORD_JD_SCORES table
    • Get JD scores for each (legal) Mesh from DB: MH_JD_SCORES table and SH_JD_SCORES table
    • Calculate Avg. JD scores for the phrase and legal Meshs for both words frequency count and document count.
  • Post-process (Output Filter):
    • Print out Input term (text and MeSH)
    • Output filter details
    • Score entries display number
    • No output message
    • Cluster option
    • JD candidates
    • Use alphabetical order for JDs have same score (Ex: "taylor", "assault")

• Sample commands:

  > jdi -itmh -d -p
  => index a text and MeSHs input from standard input with prompt and detail scores
  
  > jdi -itmh -d -f:ml -i:9801.2004.TIABMH.in -o:9801.2004.TIABMH.out
  => index text and MeSHs from file, 9801.2004.TIABMH.in, use MedLine filter options with detail scores, and send the results to a file, 9801.2004.TIABMH.out
  

• Sample Outputs:
  • a file, such as 9801.2004.TIABMH.out