| Solution Template |
Use to define a word collection. |
| Label |
Unique name for the similarity solution. |
| Name |
Field that is auto-populated with a system-assigned name
that is similar to the label name when the solution is
created. |
| Table |
Table that contains the records to use for the word
collection, for example, the Incident table or the Asset
table. When you assign a table value, a link appears that
shows the number of records that match your current
conditions. |
| Filter |
Conditions that you want to apply to the training
records. To train a solution, the filter must return at
least one record. If your filter returns no records, update
it. |
| Input Fields |
Record the fields that contain the text and context that
you want to include in your word collection. The field
data type can be a string, reference, choice, or HTML,
such as Short description and
Description.
Note: Journal type is not
a supported data type.
Good candidates for your
input fields have text that is relevant to the solution.
For example, if you are configuring a solution to find
similar incident records, you can select the
Short Description,
Description,
Resolution notes, and
Close notes
fields. |
| Training Frequency |
Training is performed once by the system, by default.
Because your data can age over time and degrade the
accuracy of recommendations, consider invoking scheduled
trainings once your solution definition is fairly
stable. |
| Domain |
On instances where domain separation is active, select
the domain whose target records you want to use for your
word collection. Create a separate similarity solution
definition record for each domain whose field values you
want to use for your word collection. |
| Similarity Fields |
Record fields that are likely to contain words and
phrases that help the system identify similar records for
your solution. To change your Similarity
Field choices, click the Lock icon
( ) to open the field and make your updates. Click
the icon again to close the field and save your
updates. |
| Similarity Window |
The period in which you want to look for similar records.
If you have a smaller number of total incoming records, a
larger window might be best. However, if the window is too
large, you may retrieve records that are not as useful. If
the window is too small, you might not retrieve enough
similar records. For example, if you are looking for
similar incident records that are open, you can select
Last 1 day. This selection
targets the most recent records, many of which could
still be open. |
| Similarity Window Filters |
Filter conditions for your similarity window. These
filters define the dataset conditions under which your
similarity results are determined. For example, if you
are looking for similar incident records that are open,
you can filter your search by creating conditions such
as: [Incident state] [is] [In
progress]
These filters are
applied in addition to the Input
Field filters. |
| Window Refresh Frequency |
Frequency to refresh the similarity window. For example,
if your window contains incident records that are open, you
can select a refresh frequency value of Every 15
minutes. New incidents typically occur
frequently throughout the day so this frequency increases
the likelihood that newly opened records are included in the
refresh. Note: If your similarity window is composed of
records such as Knowledge article records, which are
typically not created often, you can choose a larger
refresh frequency such as Every 1
day. |