Pre-Grant Publication Number: 20070282832
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Prior Art Detail
Summary / Description
| Summary / Description | Automatically discover patterns of user input entered into a web browser. |
Basic Information
| Type of Prior Art | Online Publication |
| URL | http://www10.org/cdrom/papers/2... |
| Author/Creator | Chia-Hui Chang and Shao-Chen Lui |
| Title | IEPAD: Information Extraction based on Pattern Discovery |
| Publication Date | January 1, 2001 |
| Publisher | Tenth International World Wide Web Conference, 2001 |
| Directions to Document Location | |
| Additional Information | |
Notes / To Do
| Notes | |
Excerpt
Excerpt The system IEPAD includes three components, an extraction rule generator which accepts an input Web page, a graphical user interface, called pattern viewer, which shows repetitive patterns discovered, and an extractor module which extracts desired information from similar Web pages according to the extraction rule chosen by the user. |
Relevance
Claims
1
A system that facilitates automatic tracking of user data comprising:
a keystroke capture component that captures keystrokes in the form of a character string;
an extraction component that extracts one or more character substrings having at least a minimum length of characters from the character string;
a string analysis component that analyzes the character substrings extracted from the character string to determine a frequency of occurrence for each extracted character substring; and
an order component that orders the extracted character substrings according to at least one parameter comprising the frequency of occurrence.
Relevance
This describes a broad area of machine learning known as "pattern discovery." They are attempting to discover patterns in user input in order to automatically identify "important" substrings, such as SSN. I do not see a description of their preferred pattern discovery algorithm, but the reader should be aware that hundreds of algorithms have been previously been published in the past two decades. Some are commonly used in data compression, for example in the WinZip and GIF file formats. Applying this technique to anti-phishing software may (or may not) be novel, however the technique itself is not.
This describes a broad area of machine learning known as "pattern discovery." They are attempting to discover patterns in user input in order to automatically identify "important" substrings, such as SSN. I do not see a description of their preferred pattern discovery algorithm, but the reader should be aware that hundreds of algorithms have been previously been published in the past two decades. Some are commonly used in data compression, for example in the WinZip and GIF file formats. Applying this technique to anti-phishing software may (or may not) be novel, however the technique itself is not.
Claim Chart
All
