IDOL Content Component 23.2

# Text

The query text. You can submit the following searches to IDOL Content Component:

- Conceptual Search

- Keyword Search

- Exact Phrase Search

- Boolean and Proximity Search

- Case-Sensitive Search

- Fuzzy Search

- Parametric Search

- Proper Names Search

- Soundex Keyword Search

- Synonym Search

For details on how to combine different query types and how IDOL Content Component ranks the relevance of results, refer to the IDOL Server Administration Guide.

Actions: | Query GetQueryTagValues
Type: | String
Default: |
Example: | `Text=Gene analysis discovered methods to determine the exact sequence of nucleotides that compose a specific gene`
See Also: | SplitNumbers configuration parameter UnstemmedMinDocOccs configuration parameter

## Field Restrictions

You can use `Text` to specify field restrictions for result documents, as long as the fields that you use to restrict results are Index fields (for details on Index fields, refer to the IDOL Server Administration Guide). This option also applies to XML attributes.

NOTE: You can refer to XML attributes in the following format:

    */tagName/_ATTR_attributeName)

To match multiple fields simultaneously, separate them with colons.

For example:

    Text=cat:CREATURE:FAUNA+dog:ANIMAL+rabbit:FARM/_ATTR_ANIMAL

## Wildcards

You can use the following Wildcards in query text.

- `?` to match one character.

- `*` to match zero, one, or more characters.

TIP: Use Wildcard matching only when necessary, because it can affect IDOL Content Component performance.

You can use the UnstemmedMinDocOccs configuration parameter to specify the number of documents in which a term must occur for it to be considered in a Wildcard search. You can also use the UnstemmedTrackFields configuration parameter to optimize Wildcard queries for certain fields.

NOTE: To use Wildcards to search for numbers, you must set the SplitNumbers configuration parameter to `False`.

Examples:

    Text=Mi?rotech

This query returns documents that contain the term Mikrotech or Microtech.

    Text="Wilk* Co*ins":*/Name:Author+Arm?dale:*/Title

This query returns documents that contain a `Name` or `Author` field whose value matches the Wildcard string `Wilk* Co*ins` (for example, Wilkie Collins), and documents that contain a `Title` field whose value matches the Wildcard string `Arm?dale` (for example Armadale).

Consider the following scenarios:

- `A`. The IDOL Content Component has two indexed documents. One document contains the word `rollerskating`, and the other contains the word `rollerskaters` (both of which stem to `ROLLERSK`).

- `B`. The IDOL Content Component has only one indexed document. It contains the word `rollerskater` (which also stems to `ROLLERSK`).

    Text=rollersk*

Because this query returns all documents that contain any terms that stem to `ROLLERSK`, it returns both documents in situation `A` and the one document in situation `B`.

    Text=rollerskatin*

A Wildcard query returns documents only if one or more matches for the Wildcard term exist in the documents on the IDOL Content Component. If the term is matched, it is then stemmed, and all occurrences of the stem (in any document) are also considered matches.

Therefore, with this query, both documents in situation A are returned (because `rollerskatin*` matches `rollerskating`, and because it stems to `ROLLERSK`, which has matches in both documents), but the document in situation `B` is not returned (because `rollerskatin*` does not match `rollerskater`).

`Text="rollerskatin*"` [when `AdvancedSearch=True`]

This query returns documents in which the Wildcard term is matched. However, because AdvancedSearch is enabled and the Wildcard term is in quotes, the Wildcard term is not stemmed, and additional matches to the stem are not returned.

Therefore, with this query, only the `rollerskating` document is returned in situation A, and no document is returned in situation B.

## Term Weights

You can add weights to terms in your query. IDOL Content Component returns documents that contain highly weighted terms with a higher relevance than documents that contain only terms with lower weights. Use the TermGetInfo action to find out the weight of the term. Specify weights as a number in brackets next to the term. The maximum weight is `4095`, but OpenText recommends that you use a maximum value of `511`.

For example:

    Text=Cat[50] OR Dog

This query returns documents that contain the term `cat` or the term `dog`. If the term `dog` has a higher weight than `50` in IDOL Content Component, documents that contain the term `dog` return with higher relevance than documents that contain only the term `cat`. If the term `dog` has a lower weight than `50`, documents that contain the term `cat` return with higher relevance.

    Text=Cat[30] OR Dog[10]

This query returns documents that contain the term `cat` or the term `dog`. Documents that contain only the term `cat` return a relevance value that is three times higher than documents that contain only the term `dog`.

You can apply term weights to phrases. For example:

    Text="cats and dogs"[100]

This query returns documents that contain the phrase `"cats and dogs"` and applies a weight of `100` to this phrase.

You can apply weights to terms in parentheses. In this case, the weight applies to all terms within the parentheses. For example:

    Text=(cat OR dog)[100] AND (fish OR dolphin)[150]

This query returns documents that contain at least one of the terms `cat` or `dog`, and at least one of the terms `fish` or `dolphin`. It assigns the terms `cat` and `dog` a weight of `100`, and it assigns the terms `fish` and `dolphin` a weight of `150`.

You can use multipliers to multiply the original term weight. Type a term as `*N`, where `N` is the amount to multiply by. You can use up to two decimal places. For example:

    Text=cat[*2.25] OR dog[*0.5]

This query returns documents that contain the term `cat` or the term `dog`. The term `cat` has `2.25` times its normal relevance. The term `dog` has `0.5` times its normal relevance.

You can also use any combination of these examples to apply term weights to complex phrases or expressions. For example:

    Text="cats and dogs"[*3] OR (fish[100]+dolphin[150])[*1.5]

This query applies three times the normal weight to the phrase `"cats and dogs"`. It assigns a weight of `100` to the term `fish` and a weight of `150` to the term `dolphin`. It then multiplies the weights for `fish` and `dolphin` by `1.5`.

## Occurrence Restrictions

You can restrict the documents that match a query term or phrase to documents in which the number of occurrences of the term or phrase is within a specified range. Specify the range with a colon-separated pair of numbers. The maximum value that you can specify in the range is `32000`.

For example:

    Text=Gene[3:7]

This query returns only documents in which `Gene` appears between `3` and `7` times (inclusively).

    text="Gene therapy"[5:8]

This query returns only documents in which the phrase `Gene therapy` appears between `5` and `8` times (inclusively).

    Text=Gene*[2:4]

This query returns only documents in which a term that starts with `Gene` (such as Gene or Generation) appears between two and four times (inclusively).

    Text=(Gene OR DNA)[4:8] AND Therapy

This query returns only documents in which the term `Gene` or the term `DNA` appear between `4` and `8` times (inclusively), and the term `Therapy` occurs.

You can also specify open-ended ranges. For example:

    Text="Gene therapy"[10:]

This query returns only documents in which the phrase `Gene therapy` appears 10 or more times.

You can also specify term weights and field restrictions. For example:

    text=cat[2:4]:DRETITLE + AND + cat[100][2:4]

Copyright 2023 Open Text
Version 23.2 | Last updated March 2023

Send documentation feedback

Close

Send documentation feedback

To send feedback using your default email client, open an email window.

Otherwise, send your feedback and the information below to swpdl.idoldocsfeedback@microfocus.com.

We appreciate your feedback!

Product: IDOL IDOL Content Component 23.2

Topic Title: Text