adplus-dvertising
frame-decoration

Question

What is the primary issue with analytics based on textual data?

a.

Lack of context in text analysis

b.

Lack of advanced language models

c.

High counts of words in large vocabularies

d.

Parameter smoothing given limited evidence

Posted under Big Data Computing

Answer: (d).Parameter smoothing given limited evidence Explanation:The primary issue with analytics based on textual data is parameter smoothing given limited evidence.

Engage with the Community - Add Your Comment

Confused About the Answer? Ask for Details Here.

Know the Explanation? Add it Here.

Q. What is the primary issue with analytics based on textual data?

Similar Questions

Discover Related MCQs

Q. What is the key problem with unstructured data?

Q. How is the problem of variable identification related to the analysis of textual data?

Q. Why is parameter smoothing used in analytics based on textual data?

Q. What is the main issue with the size of vocabularies in the context of textual data analytics?

Q. In image processing, what is the purpose of image segmentation?

Q. What is the key purpose of object recognition in image processing?

Q. In unstructured information processing, why is segmentation considered a prerequisite for further processing steps?

Q. What is the practical importance of novelty detection in unstructured information processing?

Q. What can object relationships include in image processing?

Q. What methodologies can be applied to processing steps in both image analysis and unstructured information processing?

Q. What is the analogous concept to image segmentation in processing unstructured information from textual documents?

Q. What is the primary level of analysis at the word level relevant for in unstructured information processing?

Q. What is analogous to object recognition in unstructured information processing from textual documents?

Q. How is scene recognition performed in textual information processing?

Q. What is information extraction primarily referred to as in computer linguistics?

Q. What is an annotation in the context of information extraction?

Q. What does "shallow" NLP primarily focus on in the context of information retrieval and extraction?

Q. For what purposes has deep NLP mainly been used in the past?

Q. In the context of computer linguistics, what is emphasized by calling the IBM Watson system "DeepQA"?

Q. What is a key component in Deep NLP systems for knowledge extraction or analysis?