Question

The training phase of a textual data mining process involves

a. removing common words from a dictionary
b. creating an attribute dictionary
c. determining whether a document is about the topic under investigation.
d. modifying an initially created attribute dictionary

Answer 1

All of the given options. The training phase of textual data mining entails determining a document's relevance to the investigated topic, which includes a thorough analysis of the text, emphasizing the importance of word choice and the use of an attribute dictionary.

Step-by-step explanation:

This involves a process of analyzing texts, media, or artifacts to examine their parts for making interpretive claims. Word choice or diction is a crucial aspect of textual analysis, where the presence and patterns of terms provide insights into the data being examined.

When engaging with textual data mining, it's essential to assume that every word may be important for the analysis, as it adds to the depth of understanding the topic. Furthermore, the process of creating, using, and possibly modifying an attribute dictionary is intrinsic to organizing and interpreting the data effectively. This involves a process of analyzing texts, media, or artifacts to examine their parts for making interpretive claims. Word choice or diction is a crucial aspect of textual analysis, where the presence and patterns of terms provide insights into the data being examined. The training phase of a textual data mining process involves determining whether a document is about the topic under investigation.