Chapter 7: Text and Web Mining

Question 1

Association

Answer 1

A popular and well researched technique for discovering interesting relationships among variables in large databases.

Question 2

Authoritative pages

Answer 2

The collective endorsement of a given page by different developers on the Web may indicate the importance of the page (Miller, 2005).

Question 3

Classification

Answer 3

A task to classify a given data instance into a predetermined set of categories (or classes).

Question 4

Clickstream Analysis

Answer 4

Analysis of the information collected by Web servers.

Question 5

Clustering

Answer 5

An unsupervised process whereby objects are classified into “natural” groups called clusters.

Question 6

Corpus

Answer 6

A large and structured set of texts prepared for the purpose of conducting knowledge discovery.

Question 7

Customer Experience Management (CEM)

Answer 7

Application designed to provide a more qualitative view of online visitor behavior, report on overall user experience, and report direct feedback given by visitors and customers.

Question 8

Deception Detection

Answer 8

Applying text mining to a large set of real-world criminal statements to develop prediction models that differentiate deceptive statements from truthful ones.

Question 9

Hubs

Answer 9

One or more Web pages that provide a collection of links to authoritative pages.

Question 10

Hyperlink-induced topic search (HITS)

Answer 10

Originally developed by Kleinberg (1999), HITS is a link-analysis algorithm that rates Web pages using the hyperlink information contained within them.

Question 11

Inverse Document Frequency

Answer 11

A common and very useful transformation that reflects both the specificity of words as well as the overall frequency of their occurrences (Manning and Schutze, 2009).

Question 12

Natural Language Processing

Answer 12

A study of the problem of “understanding” the natural human language, with the view of converting depictions of human language into more formal representations that are easier for computer programs to manipulate.

Question 13

Part-of-speech tagging

Answer 13

Also known as shallow-parsing, is the process of marking up a work in a text (corpus) as corresponding to a part of speech, based on both its definition and its context.

Question 14

Polyseme

Answer 14

Also known as homonyms, are syntactically identical words with different meaning.

Question 15

Sentiment Analysis

Answer 15

A technique used to detect favorable and unfavorable opinions toward specific products and services using many textual data sources.

Question 16

Sequence Discovery

Answer 16

Finding statistically relevant patterns between data examples where the values are delivered in a sequence.

Question 17

Singular Value Decomposition

Answer 17

Reduces the overall dimensionality of the input matrix (number of input documents by number of extracted terms) to a lower dimensional space, where each consecutive dimension represents the largest degree of variability possible (Manning and Schutze, 1999).

Question 18

Stemming

Answer 18

The process of reducing inflected words to their stem form.

Question 19

Stop Words

Answer 19

Words that are filtered out prior to or after processing of natural language data.

Question 20

Term-Document Matrix (TDM)

Answer 20

The second task in the text mining process, digitized and organized documents are used to create the TDM, where the rows represent the documents and the columns represent the terms. The relationship between the terms and documents are characterized by indices.

Question 21

Text Mining

Answer 21

A semi-automated process of extracting patters from large amounts of unstructured data sources.

Question 22

Tokenizing

Answer 22

A token is a categorized block of text. The block of text corresponding to the token is categorized according to the function it performs.

Question 23

Trend Analysis

Answer 23

A method of analysis that allows the comparison of a collection of documents to predict future trends.

Question 24

Unstructured Data

Answer 24

Data that does not have a predetermined format and is stored in the form of textual documents.

Question 25

Voice of Customer

Answer 25

See Customer Experience Management (CEM)

Question 26

Web Analytics

Answer 26

The underlying technology that provides the ability to log, parse, and report on the clickstream behavior of site visitors.

Question 27

Web Content Mining

Answer 27

A reference to the extraction of useful information from Web pages.

Question 28

Web Crawler

Answer 28

Used to read through the content of a Web site automatically.

Question 29

Web Mining

Answer 29

the process of discovering intrinsic relationships from Web data, which are expressed in the form of textual, linkage, or usage information.

Question 30

Web Structure Mining

Answer 30

the process of extracting useful information from the links embedded in Web documents. It is used to identify authoritative pages and hubs.

Question 31

Web Usage Mining

Answer 31

The extraction of useful information from data generated through Web page visits and transactions.