What is word breaking in SAP EIM-TA - SAP BusinessObjects Text Analysis?

SAP Term: word breaking

• Component: EIM-TA

• Component Name: SAP BusinessObjects Text Analysis

• Description: The process of parsing the input line into smaller, more usable pieces. By default, Data Cleanse breaks an input line on white space, punctuation, and alphanumeric transitions. Terms such as 20GB, 4G, 1st, and U2 each break into two tokens at the alphanumeric transition. For example, "20GB" breaks into "20" and "GB" tokens.

Smart SAP Assistant

• Key Concepts: 
  Word breaking is a process used in SAP BusinessObjects Text Analysis (EIM-TA) to identify and separate words from a text. It is used to analyze the text and extract meaningful information from it. Word breaking is an important part of natural language processing (NLP) and is used to identify words, phrases, and other linguistic elements in a text. 
  
  How to use it: 
  Word breaking can be used in SAP BusinessObjects Text Analysis (EIM-TA) to analyze text and extract meaningful information from it. The process involves identifying words, phrases, and other linguistic elements in a text. The extracted information can then be used for various purposes such as sentiment analysis, topic modeling, and more. 
  
  Tips & Tricks: 
  When using word breaking for SAP BusinessObjects Text Analysis (EIM-TA), it is important to ensure that the text is properly formatted and that the words are correctly identified. This can be done by using regular expressions or other methods to identify words in the text. Additionally, it is important to consider the context of the text when performing word breaking as this can help improve the accuracy of the results. 
  
  Related Information: 
  Word breaking is an important part of natural language processing (NLP). Other NLP techniques such as sentiment analysis, topic modeling, and more can be used in conjunction with word breaking to extract meaningful information from a text. Additionally, there are various tools available for performing word breaking such as regular expressions or other methods.