Free and Premium IBM C1000-012 Dumps Questions Answers

Interpret the intent behind text and returns a corresponding classification with associated confidence levels

Reduce the number of random utterances consideration, by obtaining a set of uncorrelated utterances

Translate a natural language sentence into a syntactic representation such as a parse tree

Group a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups

The Watson Discovery News configuration and documents cannot be adjusted

Documents from the Watson Discovery News collection can be ingested as sample documents to better configure a private collection

The Watson Discovery News collection is specific to the company news domain, whereas a collection is specific to a domain.

The Watson Discovery News data set and a private collection can be queried with a single query call

Make sure training images are very high resolution

Provide an approximately equal number of both positive and negative examples of pictures to train with

Ensure use of only PNG formatted images

Collect training images for the same classification that are very similar to each other

All needed information is published in the service’s online reference

From the service instance, using the IBM Cloud GUI or the Command Line Interface (CLI), or programmatically using IBM Cloud environment variables

Programmatically using the IBM Cloud registry

Connection information is found in the IBM Cloud dashboard

names of persons, places and organizations

a person’s gender based on their picture

relationships between entities

cities and geographic features

co-references between entities

Input of XML or plain text and output in JSON

Input of JSON or plain text and output in XML

Only plain text is supported for both input and output

Input of JSON or plain text and output in JSON

It is better to have multiple small collections than one big collection

The first collection uses default configuration for testing and additional collections are needed for custom configurations

To keep similar file types in their respective collections

The data may be so different that it doesn’t make sense for it all to be queried at once

When there is a need to disambiguate the output of a dialog

When there is a need to analyze or index content contained within an image

When there is a need to analyze or index content contained within speech

When there is a need to search through output from Natural Language Classifier

Personality Insights

Tradeoff Analytics

Natural Language Understanding

Discovery

parsing rules

mention detection

relation detection

part-of-speech tagging

sentence tokenization

after creating the environment

after creating the collection

after uploading sample documents

after creating a custom configuration

Use the intent from the Natural Language Classifier as part of a query

Use Natural Language Understanding to translate queries into English before searching the database

Use the Document Conversion service to search the database for the entries with the strongest relationship to the user input

Use the Discovery services to search through candidate queries and surface the ones most relevant to the user input

The system returns a low confidence score for a correct answer.

The system returns a high confidence score for an incorrect answer.

The system returns only low confidence scores for all answers.

The system returns only high confidence for all answers, both correct and incorrect.

Speech to Text and Personality Insights

Watson Assistant and Discovery

Watson Assistant and Visual Recognition

Natural Language Classifier and Visual Recognition