NEWS

Japanese Word Similarity API

2015/11/03

Announcement on ending the support service for Japanese Word Similarity API

We would like to extend our deep appreciation for a long patronage for Japanese Word Similarity API,
but we regret to inform you that we have stopped its support service since last December 3 , 2018.

Thank you for your continuing support. We will always be at your service.

By using Japanese Word Similarity API, you can create an application which calculates and returns a similarity score between two Japanese words.

Overview: Japanese Word Similarity API

Japanese Word Similarity API calculates a similarity score between the sent-in two Japanese words. The scoring criteria of this API is based on pronunciation of each word.

For example, the high similarity score is calculated to a set of words which have similar readings such as "Toukyou" and "Tokyo". The range of similarity score is from 0 to 1. And when the score is more than 0.36.., the pair is similar enough.

This similarity score is useful when disambiguating records from several data sources, whose manner of writing is different between each other.

API URL

https://labs.goo.ne.jp/api/similarity

Request parameters

Acceptable POST requests: application/x-www-form-urlencoded or application/json
※ Please be note that GET requests are not acceptable.

Parameter name Explanation
app_id(Required) Application ID
Required item
request_id request_id
Request ID
If omitted, then request_id is assumed to be “form|pos|read”
query_pair (Required) The pair of the words to analyze
Required item

An array of two strings.
ex: {query_pair : ["ウィンドウズ", "windows"]}

Response parameters

API response body: JSON format
API content-type: application/json

Parameter name Explanation
request_id Same value as request
score The similarity score between the sent-in word pair. The range of score is from 0 to 1.(Higher value means that the pair is more similar)

Input/Output sample

Input sample(application/json)

{"app_id":"[app_id]", "request_id":"record004", "query_pair":["phablet", "ファブレット"]}

Output sample

{"request_id":"record004","score":0.4836754003448215}

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