# Support and Documentation

#### Site searches

Visitors use site search pages to search for content on your site. You can include filters, sorts, and other standard features in your site-search pages, and even have different search pages for different sites.

In the previous illustration, the search results include a filter for type of content, sort options by date published, a promo associated with the search term, and the discovered items' headline and first paragraph.

Procedure. To create a site search:

2. From the Create list, select Site Search. A content edit page appears.

3. Using the following table as a reference, fill out the fields to create a site search page.

4. Click Publish.

Field

Description

Main

Title

Heading for the site search page.

Results Per Page

Number of search results per page. Previous and next buttons appear to page through the results.

Types

Content types in which this search page looks for matching items.

Filters

Fields by which visitors can filter the search results, such as date published or content type. Checkboxes appear for each filter.

Sorting

Fields by which visitors can sort the search results. If you specify sorting, Brightspot does not apply boosts.

Boosts

Criteria and matching weights for ensuring certain items appear toward the top of the search results. For more information, see Understanding relevance and boosting.

Stop Words

A list of words that do not count toward search results. For more information, see Working with stop words.

Spotlights

Dictionary

Dictionary to use for determining the spotlight associated with a search term. For information about creating dictionaries, see Dictionaries and terms.

Max Spotlights

Number of spotlights to display at the top of a search page.

By default, items without a permalink do not appear in search results. This option includes such items in the search results.

##### Understanding relevance and boosting

When a visitor searches your site for content, the number of items returned may be in the thousands. Visitors can sort the results by relevance, which orders the results by best match to the search criteria. Brightspot determines relevance using the following process:

1. Ingest the visitor's search terms.

2. Retrieve all items containing the terms.

3. Compute a relevance for each retrieved item.

4. Multiply the relevance by a boost (if any).

5. Sort the items by the boosted relevance.

Suppose a visitor wants to retrieve the previous article, and uses the search term pumpkin. Brightspot retrieves every item containing the search term, and assigns a relevance to each item. If you know that your visitors are—

• more interested in articles than any other content type, you can boost articles to make them more relevant, and they appear higher in the search results.

• more interested in newer content, you can boost new content to make those items more relevant, and they appear higher in the search results.

The following table lists some of the components used to compute relevance. The examples are simplified versions of the actual calculation. (Your version of Brightspot may use different components or relevance calculations.)

Table 18. Components affecting relevance

Component

Effect

Example

Number of items containing the term

As more items contain a term, the lower the relevance becomes.

• If 500 items contain the term pumpkin, the relevance is 1.0.

• If 1,000 items contain the term pumpkin, the relevance is 0.5.

Number of items with the field

As more items contain the field, the higher the relevance becomes.

The matching field is Headline.

• If 500 items contain the field Headline, the relevance is 1.0.

• If 1,000 items contain the field Headline, the relevance is 1.5.

Inverse item frequency

Terms that are rare over all items contribute to a higher relevance.

If pumpkin appears in only one of your items, that item receives a high relevance.

Frequency

Items with many occurrences have higher relevance than items with fewer occurrences.

Items with many occurrences of pumpkin receive a higher relevance than items with fewer occurrences.

Term saturation

As the number of occurrences grows, their contribution to relevance decreases. This component helps to prevent exaggerated relevance being assigned to documents containing many occurrences of the search term.

• Items with 100 occurrences of pumpkin have a relevance of 0.5.

• Items with 200 occurrences of pumpkin have a relevance of 0.45.

Length normalization

Compensates for the number of words in items of varying length. Without length normalization, a long item with many occurrences of the term receives a higher relevance than a shorter item, but those additional occurrences may not contribute to relevance.

An item 100 words long with the 30 occurrences of the term pumpkin receives a similar relevance as an item 1,000 words long with 300 occurrences.

Field length

As the length of a field grows, the containing item's relevance decreases.

• Item A has a headline five words long containing pumpkin.

• Item B has a headline 20 words long containing pumpkin.

Item A has higher relevance.

Average field length

As the average length of all fields containing the term increases, the containing items' relevance increases.

• The term pumpkin appears in the headline of items A and B, and the average length of those headlines is 5.

• The term pumpkin appears in the body of items C and D, and the average length of those bodies is 100.

Items C and D receive higher relevance than items A and B.

Boost

Increases the relevance for items containing the boosted term.

If the term pumpkin has a boost of 50, and the term olives has a boost of 10, items containing pumpkin are five times more relevant than items containing olives.

Brightspot does not search every field for a term. For example, when searching through images, Brightspot may not search the credits field. Contact your Brightspot administrator to determine which fields are included in searches.

The following sections describe the different types of boosts you can apply to search results.

###### Content-type boost

When you boost by content type, Brightspot increases an item's relevance if it is one of the selected content types.

Referring to the previous illustration, Brightspot increases articles' relevance by a factor of 50, and images' relevance by a factor of 30. In this scenario, articles appear higher in the search results than images.

###### Exact-match boost

When you boost by exact match, Brightspot increases an item's relevance if the exact search terms are in the selected field.

Referring to the previous illustration, Brightspot increases an item's relevance—

• by 50 if the item is an image whose caption exactly matches the search string.

• by 40 if the item is a tag whose name exactly matches the search string.

The following table describes some of the entries in the Index list.

Table 19. Boost index categories

Category

Description

AbstractAsset

Boosts matches associated with the following content types: Attachment, Image, Document, Spreadsheet, Presentation.

Boosts matches associated with a video's provider ID.

AbstractPerson

Boosts matches associated with the following content types: Author, Employee.

Boosts matches associated with an item's metadata, such as file format or file size.

AssetUsageData

Boosts matches associated with an asset's usage availability, such as approval required or expiration date.

ColorFilterData

Boosts matches associated with an image's color composition.

CreativeWork

Boosts matches associated with the following content types: Article, Blog Post, Audio, Gallery, Video, Live Blog, Press Release, Quiz Page.

DamAsset

Boosts matches associated with items shareable through Digital Asset Management.

EmbargoableData

Boosts matches associated with an item's embargo status.

SluggableData

Boosts matches associated with an items' slug.

###### Group boosts

You can design groups of boosting weights.

Group

Group weight

Item

Individual relevance

Group relevance

Text

70

Article 1

25

1750

Article 2

20

1400

Media

30

Image 1

45

1350

Image 2

30

900

Referring to the previous table—

• There are two groups: Text with weight 70 and Media with weight 30.

• During the search, Brightspot found two articles that match the criteria for the Text group. Those two articles have individual relevances of 25 and 20.

• Similarly, Brightspot found two images that match the criteria for the Media group. Those images have individual relevances of 45 and 30.

• Multiplying the individual relevances by the group weights gives the final group relevance, such as 1750 for Article 1.

• Without group boosting, the images have higher relevances than the articles. After applying the group weights, the articles' relevances are higher than the images' relevances.

The actual computations for group relevance are more complex than this example.

When you boost by newest date, Brightspot increases an item's relevance if it is the most recent selected event, such as an upload or expiration date. You typically apply this boost in conjunction with a boost for content type.

Referring to the previous example, Brightspot increases an item's relevance by 25 if it is a document, and by another 50 if that document is the most recently uploaded.

For a description of some of the entries in the Index list, see the table Boost index categories. For an explanation of the factors impacting relevance, see the table Components affecting relevance.

###### Oldest-date boost

When you boost by oldest date, Brightspot increases an item's relevance if it is the earliest selected event, such as an upload or expiration date. You typically apply this boost in conjunction with a boost for content type.

Referring to the previous example, Brightspot increases an item's relevance by 25 if it is a document, and by another 50 if that document is the earliest one uploaded.

For a description of some of the entries in the Index list, see the table Boost index categories. For an explanation of the factors impacting relevance, see the table Components affecting relevance.

###### Package boost

When you boost by a package, Brightspot increases an item's relevance if it is associated with the selected package.

Referring to the previous example, Brightspot increases an item's relevance by 75 if it is associated with the package Halloween Campaign.

###### Partial-match boost

When you boost by partial match, Brightspot increases an item's relevance if the search terms partially match the selected field. A partial match occurs when a search word begins one of the item's words. For example, if you search for cream puff, Brightspot detects a match in the following cases:

Text in item

Result

Do you drink your coffee with cream?

Found the word cream, which is one of the search terms.

With a puffed pillow, he lay down to bed.

Found the word puffed, which starts with one of the search terms.

Founds the words cream puffs, both of which start with the search terms. In this case the item gets higher relevance because it contains two search terms, while the previous items receive a lower relevance.

Given a match, Brightspot applies the weight to the relevance.

Referring to the previous illustration, Brightspot increases an item's relevance by 35 if a podcast's name is a partial match to the search string.

For a description of some of the entries in the Index list, see the table Boost index categories. For an explanation of the factors impacting relevance, see the table Components affecting relevance.

###### Section boost

When you boost by a section, Brightspot increases an item's relevance if it is associated with a section.

Referring to the previous example, Brightspot increases an item's relevance by 75 if it is associated with the package Cream Puff Recipes.

###### Semantic-match boost

When you boost by semantic match, Brightspot increases an item's relevance if the item is the indicated content type and the search terms include one or more of the keywords.

Referring to the previous illustration, Brightspot increases an item's relevance by 35 if the item is a blog post and the item includes words that start with flour, water, or yeast. The following table provides some examples.

Content type

Field and text

Result

Blog post

Body: No matter what bread you make, you'll need flour, water, and yeast.

Boosted because the content type is correct, and the search terms appear in the item.

Blog post

Title: Watering plants is a must on hot days.

Boosted because the content type is correct, and the the search term water begins one of the title's words.

Image

Caption: Freshly baked bread from whole wheat flour.

No boost because the content type is incorrect.

###### Starts-with match boost

When you boost by starts-with match, Brightspot increases an item's relevance if the search terms form the beginning of the selected field.

Referring to the previous illustration, Brightspot increases an item's relevance by 35 if the item is an image whose caption starts with the search string. If you are searing for cream puff, a boost occurs for image captions Cream puff is my favorite high-calorie snack and Cream puffs for dessert.

###### Tag boost

When you boost by tag, Brightspot increases an item's relevance if it is associated with the selected tag.

Referring to the previous example, Brightspot increases an item's relevance by 35 if it is associated with the tag Appetizers.

##### Working with stop words

Stop words are common words that you want to exclude from searches. For example, suppose you enter the following search phrase:

Brain surgeons who are really smart and who are close to me

The words who, and, are, to, and me are extremely common and do not help to distinguish one search result from another. When performing a search, Brightspot can remove those words from the phrase and then search for the following:

Brain surgeons really smart close

Removing stop words also improves relevance. An item with a lot of stop words, such as and and or, may seem very relevant compared to another item that uses less of such words—even though the actual content may be less relevant.

Procedure. To create or modify a stop-words list:
1. Search for and open your site's site search.

2. From the Stop Words selection field, select Create New. A New Stop Words widget appears.

3. In the Name field, type a name for the stop-words list.

4. Under Stop Words, add new stop words, or click |mi-remove| to remove existing ones.

5. Click Save.