Search tips to help you find content more easily

There are a number of operands you can use to optimize your search for content in the CodeSecure Support Portal

Search Tips

• Find multiple words: Use double quotes (") around each word to find content that contains all those words.
  For example, "article" "title" "section" "author" retrieves content that contains all four words, in any order.  Make sure you put spaces between the search words, otherwise the search handles the text as one string. 
  You'll get hits if there is a stemmed version of a word (e.g. articles). You won't get hits where content contains only the words title and section, for example.  
  If you use single quotes (') around a word, the single quotes are ignored.  If you search for 'article' 'title' 'section' 'author', you'll see hits for all content that contains any of the words title or article or section or author (exactly as if you had searched without the single quotes).
• Find a phrase: Use double quotes (") around a phrase to find content that contains all the words in that phrase.
  For example, "article title" retrieves all content that contains the words article and title, in that order.  You'll also get hits if there is a stemmed version of the word (e.g. articles).  You won't get hits where content contains only the word title, for example.
  If you use single quotes (') around a phrase, the single quotes are ignored. 
• Exclude results containing certain words: Use the minus operator (-) in front of the search term to find content that does not include that word or phrase.
  For example, reporting bugs -support returns content containing the words reporting and bugs, but excludes those that contain the word support from the result set.
• Combine operands for advanced search: you can combine the operands above to find a very specific set of results.
  For example, "reporting bugs" -support returns hits for content that contains both the words reporting and bugs, but does not contain the word support.

The fine print

The ranked search results are based on relevance scores and are displayed in descending order of their scores.

Relevance scores are indicated by a weighted average per field score. A field is a part of a record, representing an item of data. Some examples are:

• Matches in an article or post title field score higher than matches in other fields.
• Matches in article labels score higher than matches in the body field.

These are the current field weights:

Relevance scores are also impacted by a text analysis process that considers the following factors:

• Exact match - Results that exactly match a word in the search string. This scores higher than a stemmed match.
• Stemmed match - Results where a word matches after stemming. For example, the plural form of a word generally matches the singular form.
• Term frequency - Number of matches returned in a single field. Higher term frequency increases the score.
• Field length - Matches in shorter fields score higher than results in longer fields. For example, if you have a single word search, that matches a one-word title, that will score higher than a hit in a long article title with many words.
• Proximity boost - The score is boosted when all the search terms are close together in the same field. For example if all the search terms are included in an article title this puts them in close proximity and gives the result higher relevance.
• Phrase boost - In multiple term queries, exact word order is preferred. For example, when searching for “car park”, results containing “car park” are ranked higher than results containing “park car.”
• Query length - For one and two word queries, the algorithm returns only documents that match all the search words. For longer queries, 40% of the query terms must be present in a document for it to become a search result.
• Overall quantity and quality of relevant results.