Search results
Results from the WOW.Com Content Network
An access key allows a computer user to immediately jump to a specific part of a web page via the keyboard. On Wikipedia, access keys allow you to do a lot more—protect a page, show page history, publish your changes, show preview text, and so on.
In computing, a keyboard shortcut is a sequence or combination of keystrokes on a computer keyboard which invokes commands in software.. Most keyboard shortcuts require the user to press a single key or a sequence of keys one after the other.
Word wrap is the additional feature of most text editors, word processors, and web browsers, of breaking lines between words rather than within words, where possible. Word wrap makes it unnecessary to hard-code newline delimiters within paragraphs, and allows the display of text to adapt flexibly and dynamically to displays of varying sizes.
Document retrieval is defined as the matching of some stated user query against a set of free-text records. These records could be any type of mainly unstructured text, such as newspaper articles, real estate records or paragraphs in a manual. User queries can range from multi-sentence full descriptions of an information need to a few words.
Pluma is a graphical application which supports editing multiple text files in one window (tabs or MDI). It fully supports international text through its use of the Unicode UTF-8 encoding. As a general purpose text editor, Pluma supports most standard editor features, and emphasizes simplicity and ease of use.
In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references).
After pre-processing the text data, we can then proceed to generate features. For document clustering, one of the most common ways to generate features for a document is to calculate the term frequencies of all its tokens. Although not perfect, these frequencies can usually provide some clues about the topic of the document.
Each ij cell, then, is the number of times word j occurs in document i. As such, each row is a vector of term counts that represents the content of the document corresponding to that row. For instance if one has the following two (short) documents: D1 = "I like databases" D2 = "I dislike databases", then the document-term matrix would be: