Controls: show

Document

Comments:

[log in] or [register] to leave a comment for this document.


Go to: all documents

Options: show

Contact:

mail@internetcommons.ca

Website:

[home] [about] [help]

Subsites:
Members:

[profiles] [forum]

Document

Finding Content

16-Nov-2012 [28]

Part of Documentation

Classic Searching

Every system list in Muster Wiki has search capability, within the scope of each list. These include content record types -- documents, blog posts, pictures, document files, document extracts, external links, widgets -- and container record types -- topics, folders, and blogs. Also there's a database list to search all items (other than pictures and blogs, but including blog posts), and a library list to search all external resources (other than pictures). Treetops and folder treetops have searches for all topics and folders respectively.

Finally, the home page (if your Webmaster has used the default Home Page Search capability) has both the database search and a google search.

The searches on system lists are keyword searches. That is they search for the exact words entered (and ignore words that are less than four characters long). So for instance plurals are not searched from singular keywords. "Campfire" and "Campfires" will yield quite different results. A way to increase flexibility for plurals is to add an asterisk at the end of singular words, which is treated as a wild card character for any number of characters following the characters at the start of the word. So "Camp*" would find "Camp", "Camps", "Campfire", "Campfires", and "Camping" (and "Campers", and "Campy"...). For a complete list of syntax helpers, click on the question mark beside each keyword input field for a popup help box.

The order of the returned result set is determined by relevance in two ways. First, the first fields considered are those that would likely carry the most weight in meaning: Title and Caption. Then Description and Location are considered, and finally the Body (markup) field. Second, each of these groups is weighted by the number of words that are found, in cascading order. Any ties are sorted by Date and Title in that order.

The results are usually pretty good.

Google Search

If your site has been crawled by Google, then you can use the Google search box as well (if included by your Webmaster). This search essentially generates a google "site:" search.

Specialized Searches

Some specialized searches are restricted by permissions.

There are a number of specialized searches on content record and container record lists. First, each list provides a "My recordtype" button, that will find records with you as the author. In addition, there is a dropdown field selection under the keyword field that offers many search constraints: Published, Unpublished, Drafts, Requested, Declined, Hidden, Trashed, Open author notes, and Open followup notes. Some lists offer Administrators a "Recent Updates" list.

The Database list has a "Field Search" option for a choice of Title, Caption, Location, Source Text, URL, Filename, Description, and Body (markup) fields. This searches for exact character sequences anywhere within the field, whether or not these character sequences form a word.

Finally, the Pictures and Document files lists offer a "Filename" search, in which one can search for a complete or partial filename (case insensitive) to determine if a file has already been uploaded.

An Alternative Search Strategy - Hunting

Another way of finding something in a Muster Wiki website is to go hunting. Because records can be added to several topics, depending on the organization and subject matter of a website, this can sometimes be very successful. For example if a person is looking for information on campfire permits in a website about city parks, they could look in both a "Campfires" topic, and a "Permits" topic, and likely find the "Campfire Permits" record they are looking for.

Put another way, website custodians have the opportunity to make natural semantic links using Muster Wiki, that would roughly mimic their understanding of the natural semantic web of the subject matter.