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Process for applying pattern recognition to repeated copy and paste

IP.com Disclosure Number: IPCOM000199542D
Publication Date: 2010-Sep-08
Document File: 3 page(s) / 45K

Publishing Venue

The IP.com Prior Art Database

Abstract

It is often the case that someone copies an item to their clipboard with the intention of pasting it several times and then making a small change to each pasted item. For example a user may copy a line of text and paste it several times, making a change to each line once pasted. This is prone to user error, and it is time consuming to perform this repeated task manually. The proposed solution below overcomes these drawbacks by automating this process.

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Process for applying pattern recognition to repeated copy and paste

It is often the case that someone copies an item to their clipboard with the intention of pasting it several times and then making a small change to each pasted item. For example a user may copy a line of text and paste it several times, making a change to each line once pasted. This is prone to user error, and it is time consuming to perform this repeated task manually. The proposed solution below overcomes these drawbacks by automating this process.

    The solution involves recognising a pattern in the changes made to items pasted multiple times. This is done by finding the pattern of differences between the original and each of the edited pastes, which can then be applied to the succeeding items.

A simple example of this is a line of text with one of the words changed:
*1 - Original line copied to clipboard: "This is topic five"
*2 - First paste with one change made:"This is topic six"
*3 - Second paste with one change made: "This is topic seven"
*4 - A pattern has been identified and the user is prompted and they accept that the pattern is correct.
*5 - Third paste with one change made automatically based on the accepted pattern: "This is topic eight"

    Another example is when writing code the system could determine if the changes correlate to the items in collections in scope - e.g: the members of an array. This example has the benefit of potentially being able to determine how many times the user would like to paste their item, e.g: once per member, as the size of the collection may be known.

    This could equally be applied to binary files, such as audio or images, as patterns can be determined in changes between versions of these data files.

    When a user copies an item to their clipboard it is stored and recorded as the original version.

The item is pasted and changes made to each paste are recorded until a pattern in the differences it detected.

This pattern can then be applied to the succeeding pasted items automatically (if the user accepts the pattern) rather than the user editing them manually.

    Patterns can be recognised when a user's behaviour is predictable. For example: the original item is 'x', the first paste is edited to 'y', the second paste is edited to 'z', and so a prediction can be made that the next item will be: 'z' with the pattern applied.

    The following is an example to explain the system when implemented as a plug-in for an IDE to recognise when a user performs a pattern of behaviour which relates to an array or collection.

    The user starts with a class which has an array of words declared at the top, and a main method.

The class is as shown below:
import java.util.*;
public class SimpleClass
{
private static String[] someWords = {"ant", "bat", "cat", "dog", "elk", "frog", "goat"};
public static void main(String[] args)
{

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    System.out.println("Main started"); }

    For the steps below in this example only the main method is shown, as the rest of the...