.:] irrelavent.relevency [:. « beef.b10g-2.0.0

.:] irrelavent.relevency [:.

August 8th, 2007 – 13:37:52

So it seems like everyone has there little voodoo algorithms on how to calculate how relevant a search result is to the term that was being searched, and I personally, do not think it should be thus. So I am going to share my rough draft for a simple relevancy calculation between a String, hereafter reffered to as query, and a search result, hereafter referred to as SearchResultVO.

First we must define our SearchResultVO

class SearchResultVO {
   private String title;
   private String description;
   private String tags;
   private String content;

   // ... insert constructor, getters and setters here. it`s your everyday bean ... //
}

Alright, awesome, so what do we need next, well, I think we should use a simple regex routine to count the number of times one string occurs in another string. Pretty simple little routine that is very re-usable.

public static int occurances(String search, String subject, boolean caseInsensitive) {
   Pattern pattern = null;
   if (caseInsensitive) {
      pattern = Pattern.compile(search, Pattern.CASE_INSENSITIVE);
   } else {
      pattern = Pattern.compile(search);
   }

   int count = 0;
   Matcher matcher = pattern.matcher(subject);
   while ( matcher.find() ) {
      count ++;
   }
   return count;
}

POOF!

Now we have our simple utility routine…

Next step, the relevancy calculator itself.

/* First define some constants for weight -- Obviously, you will want to play with these values for your own implementation, and maybe even introduce more weight factors, like what site the result is coming from, etc. */
private static final double TITLE_WEIGHT = 2.5d;
private static final double DESC_WEIGHT = 1.3d;
private static final double CONTENT_WEIGHT = 1.0d;
private static final double TAG_WEIGHT = 2.0d;

public static double calculateRelevancy(String query, SearchResultVO result, boolean caseInsensitive) {
   double relevancy = 0d;

   // Split the query into individual `words` by any whitespace
   String [] tokens = query.split("\s");

   // Iterate over the tokens
   for (int i =0, size=tokens.length; i < size; i ++) {
      relevance += occurances(tokens[i], result.getTitle(), true) * TITLE_WEIGHT;
      relevance += occurances(tokens[i], result.getDescription(), true) * DESC_WEIGHT;
      relevance += occurances(tokens[i], result.getContent(), true) * CONTENT_WEIGHT;
      relevance += occurances(tokens[i], result.getTags(), true) * TAG_WEIGHT;
   }

   return relevance;
}

Obviously this is a bare minimum pattern, but will give you fairly accurate results. You can add to this fairly easily by calculating full term relevancy (usually heavily weighted), using different kinds of string parsing to manipulate the query such as looking for things like a + or - or “” and searching those things in particular, of course, if you search engine is working correctly, you should need to worry about most of those issues but you may have a different application where you need a granular scoring system without the search engine function, or whatnot.

Let me know how you would customize this to make it more accurate and more granular, it would be interesting to come up with something that people could just plug into their application to determine relevancy between two things.

Comments are definately appreciated!

Posted by: beef | Comments: (74)

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