Exam 7: Text Analytics, Text Mining, and Sentiment Analysis

What types of documents are BEST suited to semantic labeling and aggregation to determine sentiment orientation?

When identifying the polarity of text, the most granular level for polarity identification is at the ________ level.

All of the following are challenges associated with natural language processing EXCEPT

In the security domain, one of the largest and most prominent text mining applications is the highly classified ECHELON surveillance system. What is ECHELON assumed to be capable of doing?

In the financial services firm case study, text analysis for associate-customer interactions were completely automated and could detect whether they met the company's standards.

Natural language processing (NLP), a subfield of artificial intelligence and computational linguistics, is an important component of text mining. What is the definition of NLP?

________, also called homonyms, are syntactically identical words with different meanings.

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.

Sentiment classification usually covers all the following issues EXCEPT

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.

During information extraction, entity recognition (the recognition of names of people and organizations) takes place after relationship extraction.

The bag-of-words model is appropriate for spam detection but not for text analytics.

________ is a technique used to detect favorable and unfavorable opinions toward specific products and services using large numbers of textual data sources.

In the opening vignette, the architectural system that supported Watson used all the following elements EXCEPT

What application is MOST dependent on text analysis of transcribed sales call center notes and voice conversations with customers?

When labeling each term in the WordNet lexical database, the group of cognitive synonyms (or synset) to which this term belongs is classified using a set of ________, each of which is capable of deciding whether the synset is Positive, or Negative, or Objective.

How would you describe information extraction in text mining?

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?

In text mining, which of the following methods is NOT used to reduce the size of a sparse matrix?

When viewed as a binary feature, ________ classification is the binary classification task of labeling an opinionated document as expressing either an overall positive or an overall negative opinion.