The Database Quiz

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1.   Regional accents present challenges for natural language processing
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The Database Quiz - Quiz

A database is a structured set of electronic data held in a computer and not physically tangible. The database quiz below is for all the techies who are revising for their database exams. Take it up and all the best.

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2.   In text mining, inputs to the process include unstructured data such as Word documents, PDF files, text excerpts, e-mail and XML files
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3.  Current use of sentiment analysis in voice of the customer applications allows companies to change their products or services in real time in response to customer sentiment. 
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4.   In sentiment analysis, it is hard to classify some subjects such as news as good or bad, but easier to classify others, e.g., movie reviews, in the same way. 
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5.   In text mining, if an association between two concepts has 7% support, it means that 7% of the documents had both concepts represented in the same document
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6. Chinese, Japanese, and Thai have features that make them more difficult candidates for natural language processing
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7.   Articles and auxiliary verbs are assigned little value in text mining and are usually filtered out
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8.  The bag-of-words model is appropriate for spam detection but not for text analytics. 
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9.  According to a study by Merrill Lynch and Gartner, what percentage of all corporate data is captured and stored in some sort of unstructured form
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10. .  In text analysis, what is a lexicon? 
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11. .  In text mining, stemming is the process of 
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12. Categorization and clustering of documents during text mining differ only in the preselection of categories
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13. .  What application is MOST dependent on text analysis of transcribed sales call center notes and voice conversations with customers? 
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14.  What data discovery process, whereby objects are categorized into predetermined groups, is used in text mining? 
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15.  All of the following are challenges associated with natural language processing EXCEPT 
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16. .  In sentiment analysis, which of the following is an implicit opinion?
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17.  4.  During information extraction, entity recognition (the recognition of names of people and organizations) takes place after relationship extraction
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18. .  In text mining, tokenizing is the process of 
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19.  Inputs to speech analytics include all of the following EXCEPT 
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20.   Which of these applications will derive the LEAST benefit from text mining
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21.   The linguistic approach to speech handles processes elements such as intensity, pitch and jitter from speech recorded on audio
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22. .  How is objectivity handled in sentiment analysis? 
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23.   Text analytics is the subset of text mining that handles information retrieval and extraction, plus data mining
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24. .  In text mining, creating the term-document matrix includes all the terms that are included in all documents, making for huge matrices only manageable on computers
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25.   Sentiment classification usually covers all the following issues EXCEPT 
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26.   What do voice of the market (VOM) applications of sentiment analysis do? 
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27. In sentiment analysis, sentiment suggests a transient, temporary opinion reflective of one's feelings
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28.  Identifying the target of an expressed sentiment is difficult for all the following reasons EXCEPT 
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29.  Detecting lies from text transcripts of conversations is a future goal of text mining as current systems achieve only 50% accuracy of detection. 
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30. .  In text mining, which of the following methods is NOT used to reduce the size of a sparse matrix? 
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31.   What types of documents are BEST suited to semantic labeling and aggregation to determine sentiment orientation? 
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  Regional accents present challenges for natural language...
  In text mining, inputs to the process include unstructured data...
 Current use of sentiment analysis in voice of the customer...
  In sentiment analysis, it is hard to classify some subjects...
  In text mining, if an association between two concepts has 7%...
Chinese, Japanese, and Thai have features that make them more...
  Articles and auxiliary verbs are assigned little value in text...
 The bag-of-words model is appropriate for spam detection but not...
 According to a study by Merrill Lynch and Gartner, what...
.  In text analysis, what is a lexicon? 
.  In text mining, stemming is the process of 
Categorization and clustering of documents during text mining differ...
.  What application is MOST dependent on text analysis of...
 What data discovery process, whereby objects are categorized...
 All of the following are challenges associated with natural...
.  In sentiment analysis, which of the following is an implicit...
 4.  During information extraction, entity recognition (the...
.  In text mining, tokenizing is the process of 
 Inputs to speech analytics include all of the following...
  Which of these applications will derive the LEAST benefit from...
  The linguistic approach to speech handles processes elements...
.  How is objectivity handled in sentiment analysis? 
  Text analytics is the subset of text mining that handles...
.  In text mining, creating the term-document matrix includes all...
  Sentiment classification usually covers all the following...
  What do voice of the market (VOM) applications of sentiment...
In sentiment analysis, sentiment suggests a transient, temporary...
 Identifying the target of an expressed sentiment is difficult...
 Detecting lies from text transcripts of conversations is a...
.  In text mining, which of the following methods is NOT used to...
  What types of documents are BEST suited to semantic labeling...
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