> For the complete documentation index, see [llms.txt](https://docs.zingg.ai/zingg/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zingg.ai/zingg/versions/enterprise-v0.6.0/improving-accuracy/stopwordsremoval.md).

# Ignoring Commonly Occuring Words While Matching

Common words like Mr, Pvt, Av, St, Street etc. do not add differential signals and confuse matching. These words are called **stopwords** and matching is more accurate when stopwords are ignored.

The stopwords can be recommended by Zingg by invoking:

`./scripts/zingg.sh --phase recommend --conf <conf.json> --column <name of column to generate stopword recommendations>`

The stopwords generated are stored at the location - models/100/stopWords/columnName. This will give you the list of stopwords along with their frequency.

By default, Zingg extracts 10% of the high-frequency unique words from a dataset. If the user wants a different selection, they should set up the following property in the config file under the respective field for which they want stopwords:

```
stopWordsCutoff: <a value between 0 and 1>
```

Once you have verified the above stop words, you can configure them in the JSON variable **stopWords** with the path to the CSV file containing them. Please ensure while editing the CSV or building it manually that it should contain *one word per row*. Also, ensure that it has a header such as StopWords as Zingg ignores the header by default and works on the remaining data.

```
"fieldDefinition":[
   	{
   		"fieldName" : "fname",
   		"matchType" : "fuzzy",
   		"fields" : "fname",
   		"dataType": "string",
   		"stopWords": "models/100/stopWords/fname.csv"
   	},
```

In case of stopwords being set up manually by the user, the list of stopwords may consider multiple columns and Zingg used only the first column by default.

For recommending stopwords in **Zingg Enterprise Snowflake**,

`./scripts/zingg.sh --phase recommend --conf <conf.json> --properties-file <path to Snowflake properties file> --column <name of column to generate stopword recommendations>`

The stopwords generated are stored in the table - zingg\_stopWords\_columnName\_modelId where we can see the list of stopwords and their frequency associated with the given column name.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.zingg.ai/zingg/versions/enterprise-v0.6.0/improving-accuracy/stopwordsremoval.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.