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NEW QUESTION: 1
個人または組織が組織の業界に関連する適切な商慣行に従事することを必要とする管理ポリシー管理はどれですか
A. 職務分離
B. 知っておくべきこと
C. 十分な注意
D. 職務の分離
Answer: C

NEW QUESTION: 2
Welche der folgenden Praktiken unterstützt BEST das Erreichen der Ziele des Informationssicherheitsprogramms in der IT-Funktion?
A. Abmeldung des IT-Managements von Richtlinien zur Informationssicherheit
B. Kontinuierliche Sicherheitsüberprüfung von IT-Serviceprozessen
C. Teilnahme von IT-Stakeholdern am Lenkungsausschuss für Sicherheitsprogramme
D. Überprüfung und Genehmigung von IT-Projekten durch den Informationssicherheitsmanager
Answer: C

NEW QUESTION: 3
You plan to create a bot that will support five languages. The bot will be used by users located in three different countries. The bot will answer common customer questions. The bot will use Language Understanding (LUIS) to identify which skill to use and to detect the language of the customer.
You need to identify the minimum number of Azure resources that must be created for the planned bot.
How many QnA Maker, LUIS and Language Detection instances should you create? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Sample D-UN-OE-23 Questions
Answer:
Explanation:
Sample D-UN-OE-23 Questions
Explanation
Sample D-UN-OE-23 Questions
QnA Maker: 5
If the user plans to support multiple languages, they need to have a new QnA Maker resource for each language.
LUIS: 5
If you need a multi-language LUIS client application such as a chatbot, you have a few options. If LUIS supports all the languages, you develop a LUIS app for each language. Each LUIS app has a unique app ID, and endpoint log. If you need to provide language understanding for a language LUIS does not support, you can use Microsoft Translator API to translate the utterance into a supported language, submit the utterance to the LUIS endpoint, and receive the resulting scores.
Language detection: 1
The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
This capability is useful for content stores that collect arbitrary text, where language is unknown. You can parse the results of this analysis to determine which language is used in the input document. The response also returns a score that reflects the confidence of the model. The score value is between 0 and 1.
The Language Detection feature can detect a wide range of languages, variants, dialects, and some regional or cultural languages. The exact list of languages for this feature isn't published.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/overview/language-support
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-language-support
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-language