{"componentChunkName":"component---node-modules-carrotsearch-gatsby-theme-apidocs-templates-documentation-page-js","path":"/label-dictionary/","result":{"data":{"html":{"frontmatter":{"id":"label-dictionary","title":"Label dictionary"},"html":"
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Label dictionary

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\n The label dictionary lets you tune the labels Lingo3G chooses to describe\n clusters. Using the label dictionary, you can prevent Lingo3G from selecting\n certain words or phrases, such as domain-common phrases and abusive\n language. You can also boost other labels, such as brand names.\n

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\n Lingo3G\n reads the label\n dictionary from a JSON file named\n language.labels.json, where language is the\n language name. The label dictionary must be an array of objects with the\n following structure:\n

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[\n  // zero or more includes.\n  {\n    \"include\": \"relative-path-to-include.json\",\n    \"required\": true\n  },\n\n  // zero or more weighted matcher entries.\n  {\n    \"comment\": \"Optional comment.\",\n    \"weight\": 0,\n\n    // One or more label matchers\n    \"exact\": [],\n    \"glob\": [],\n    \"regexp\": []\n  }\n]
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The structure of a Lingo3G label dictionary.

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Each object in the array must be of one of the following types:

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include
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\n Includes all entries from another label dictionary into this dictionary.\n You can use includes to split a large label dictionary into smaller ones\n or extract a common part of a set of label dictionaries.\n

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{ \"include\": \"name.json\", \"required\": true }
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include
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\n (required) Path to the label dictionary to include, relative to the\n location of this dictionary.\n

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required
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\n If true and the file to include does not exist, Lingo3G\n will trigger an error.\n

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\n If false, Lingo3G will ignore a non-existing include\n file.\n

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weighted rules
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\n Defines one or more\n label matchers\n and their associated label weight. If a label matches any rule in any\n matcher, Lingo3G applies the weight to the label.\n

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{\n  \"comment\": \"Comment\",\n  \"weight\": 0,\n\n  \"exact\": [],\n  \"glob\": [],\n  \"regexp\": []\n}
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weight
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The weight to apply to the matching labels.

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\n A weight of 0 excludes the labels from processing – Lingo3G\n will not use the labels to describe clusters. Weights between 0 and\n 1 decrease the chances that the corresponding labels appear in\n clusters. Values larger than 1 increase the likelihood that Lingo3G\n selects the labels to describe a cluster.\n

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\n If you don't specify the weight, Lingo3G assumes the\n weight of 0 and removes all the matching labels from processing.\n

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glob, exact, regexp
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\n Label matchers that\n determine to which labels to apply the weight. You can use any\n combination of the available matcher types.\n

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comment
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An optional comment for this dictionary section.

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\n If a label matches multiple rules with different weights, Lingo3G applies\n the lowest weight. For example, if a specific label matches two rule set\n with weight 0 and 2.5, Lingo3G uses the zero weight and removes the label\n from processing.\n

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A real-world label dictionary can look like this:

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[\n  { \"include\": \"common-legal-jargon.json\", \"required\": true },\n  {\n    \"comment\": \"Remove common expressions.\",\n    \"weight\": 0,\n    \"exact\": [\n      \"main page\"\n    ],\n    \"glob\": [\n      \"* home page *\",\n      \"{fnc}\", \"+ {fnc}\", \"{fnc} +\",\n      \"* banned *\"\n    ],\n    \"regexp\": [\n      \"\\\\d{1,2}(am|pm)\"\n    ]\n  },\n  {\n    \"comment\": \"Boost product names.\",\n    \"weight\": 2,\n    \"exact\": [\n      \"Lingo3G\", \"Lingo4G\"\n    ],\n    \"glob\": [\n      \"* text clustering *\"\n    ]\n  }\n]
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Example label dictionary.

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\n With the above dictionary, Lingo3G removes from processing the following\n labels: main page, Welcome to the home page,\n for clustering, 5pm and promotes the following labels in\n the clusters: Lingo3G, Lingo4G,\n text clustering tools.\n

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\n See the\n label matchers section for\n more examples of label matching.\n

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