ITE 406 - Midterm + Finals

a subfield of natural language processing and machine learning that emerged as a powerful tool for uncovering latent thematic structures within textual information

• topic modeling

• text modeling

• topic mining

• text mining

traditional methods of text analysis often never fall short when confronted with large-scale textual data

• True

• False

Answer explanation

often fall short

Topic modeling is a subfield of unsupervised machine learning

• True

• False

is a statistical technique used to discover abstract topics within a corpus of documents

• topic modeling

• text modeling

• topic mining

• text mining

it is capable of scanning a set of documents, detecting word and phrase patterns within them, and automatically clustering word groups and similar expressions that best characterize a set of documents

• topic modeling

• text modeling

• topic mining

• text mining

the reason why topic modeling is considered as 'unsupervised' machine learning because it doesn’t require a predefined list of tags or training data that’s been previously classified by humans

• True

• False

topic modeling operates on the premise that documents are:

• mixture of topics

• topics are mixture of words

• topics are mixture of phrases

the key principles underlying topic modeling:

• documents contains a mixture of topics

• topics consist of a distribution of words

• distribution of words within topics is used to identify topics in documents

• topics consist of a distribution of phrases

• distribution of phrases within topics is used to identify topics in documents

The/This probabilistic approach to modeling allows us to uncover latent topics in the data by estimating the probability of word co-occurrences.

• True

• False

• Topic Modeling Algorithms:

• - assumes that each document is a mixture of topics, and each topic is a mixture of words

• - identifies topics by maximizing the likelihood of the observed data, effectively finding groups of words that co-occur together

• LDA

• NMF

• LSA

• pLSA

• HDP