FINAL EXAM CS410 QUESTIONS AND CORRECT ANSWERS

FINAL EXAM CS410 QUESTIONS AND
CORRECT ANSWERS



(7.1) Which of the following word pairs are paradigmatically related?
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Check all that apply.
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[] car, drive
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[] computer, laptop
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[] car, vehicle
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[] computer, keyboard - ans-
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* computer, laptop: these word pairs tend to occur in the same context. We would g
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enerally not obtain a meaningful sentence by subbing "laptop" and "keyboard"
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* car, vehicle
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(7.2) Which of the following are syntagmatically related? Check all that apply.
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* computer, keyboard
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* car, vehicle
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* computer, laptop
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* car, drive - ans-* computer, keyboard: these words tend to co-
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occur in the same sentences
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* car, drive
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(7.3) Suppose the pseduo-
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document representations for the contexts of terms A and B in the vector space mo
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del are given as follows:
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dA = (0.3, 0.2, 0.4, 0.05, 0, 0.05)
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dB = (0.4, 0.1, 0.3, 0, 0.2, 0)
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What is the EOWC similarity score?
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* 0.26
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* 0.32
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* 0.40
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* 0.22 - ans-0.3*0.4 + 0.2*0.1 + 0.4*0.3 + 0 + 0 + 0 = 0.26
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(7.4) T/ sw


F: adding IDF weighting to the EOWC similarity function will penalize common words
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in the corpus - ans-True: IDF Favors rare words and penalizes common words
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, (7.5) T/F: the EOWC score is non-negative and cannot exceed 1 - ans-
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True: the EOWC score is the probability that two randomly selected words from the
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two pseudo- sw


documents are the same. Since it is a probability, its values range between 0 and 1
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w(inclusive)

(7.6) Which of the following is NOT the reason that NLP is difficult?
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* word-level ambiguity, such as the word "design" can be a noun or a verb
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* syntactic ambiguity, such as PP attachment
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* coreference resolution, such as reference of "he", "she" or "it"
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* difficulty of transforming non-text data into text data - ans-
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* difficulty of transforming non-
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text data into text data: this is not the main issue of NLP
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(7.7) Which of the following statements about NLP is correct?
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* for English, parsing POS-
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tagging with 100% accuracy is possible if computing resource and time is unlimited
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* POS-tagging is considered to be deep NLP
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* shallow NLP tends to be robust, while deep NLP doesn't scale up well
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* summarization and translation are considered to be shallow NLP - ans-
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* shallow NLP tends to be robust, while deep NLP doesn't scale up well: deep NLP
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are much more complicated and difficult
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(7.8) For sentiment analysis (opinion mining), which kind of text representation is ge
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nerally used? sw


* words, syntactic structures, entities, and relations
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* string
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* words and syntactic structures
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* words - ans-* words, syntactic structures, entities, and relations
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(7.9) Paradigmatic related words have:
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* high co-occurrence
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* high context similarity - ans-* high context similarity
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ex: Monday, Tuesday, Wednesday
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(7.10) Which of the following help to improve EOWC? Check all that apply:
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[] use sublinear transformation of term frequency
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[] reward matching rare words and discount matching frequent ones - ans-
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* use sublinear transformation of term frequency: the increase of EOWC is smaller f
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or higher TF
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* reward matching rare words and discount matching frequent ones: this favors rare
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words