Title: Knowledge Web
Patent App Number: US Patent Application 20050086188
Filed: October 1, 2003
PCT filed: April 10, 2002
WIPO priority dates: April 11, 2001 & Dec. 21, 2001 (see parent case)
Parent case: (WO/2002/084590) Knowledge Web
Inventor(s): Daniel W. Hillis & Bran Ferren
Assignee: Not identified in USPTO application but Applied Minds, Inc. is identified as an applicant in parent case.
Prior art description: The problem of finding accurate, relevant, and appropriate information on the Web Φ
Abstract:
"A system and method for organizing knowledge in such a way that humans can find knowledge, learn from it, and add to it as needed is disclosed. The exemplary system has four components: a knowledge base, a learning model and an associated tutor, a set or user tools, and a backend system. The invention also preferably comprises a set of application programming interfaces (APIs) that allow these components to work together, so that other people can create their own versions of each of the components. In the knowledge web a community of people with knowledge to share put knowledge in the database using the user tools. The knowledge may be in the form of documents or other media, or it may be a descriptor of a book or other physical source. Each piece of knowledge is associated with various types of meta-knowledge about what the knowledge is for, what form it is in, and so on."
Blogger comment(s):
The inventors began globally filing patents in 2001 with the World Intellectual Property Organization (WIPO). But, with the lone exception of the subject patent application, they did not keep up the patent application fees. That is, only the subject USPTO patent application for “Knowledge web” remains. The USPTO patent fees for the subject patent application were paid on January 18, 2008. This heralds that the USPTO will issue a patent out of the application though it will not be enforceable beyond U.S. borders. See The Funding of the Emerging Semantic Web posted elsewhere on this blog site.
Independent claims (as numbered):
1. A system for organizing knowledge in such a way that users can find knowledge, learn from it, and add to it as needed, comprising: a knowledge base comprising knowledge, meta-knowledge that was created at a time of entry of said knowledge, and meta-knowledge in the form of one or more annotations that accumulate over time, said annotations including any of, but not limited to, usefulness of said knowledge, additional user opinions, certifications of veracity of said knowledge, commentary by users, and connections between said knowledge and other units of knowledge; a set of user tools comprising one or more tools for entering said knowledge, said meta-knowledge, and said one or more annotations into said knowledge base; and a user learning model comprising any of information on a user's needs, capabilities, knowledge, and preferences, said meta-knowledge stored in said knowledge base, and generalized knowledge about how people learn.
3. A method for organizing knowledge in such a way that users can find it, learn from it, and add to it as needed, comprising any of the steps of: finding chains of explanations that connect concepts a user needs to learn to what said user already knows; showing said user a map of what said user needs to learn; choosing explanatory paths that match said user's preferred style of learning, optionally including any of enough side paths, interesting examples, multimedia documents, and related curiosities to match said user's level of interest; whenever possible, following explanatory paths laid down by great teachers; if an explanation does not work, and consistently raises a particular type of question, then recording this information in a database where it can be used in planning paths of other students; once said user has learned said concepts, updating said database to indicate that said user has recently learned said concepts; reinforcing said user's learning by finding connections that tie said concepts together; keeping track of changes in said user's preferred style of learning and pre-existing knowledge; when an explanation does not work, trying another approach; said user performing any of probing further, requesting examples, and living said database explicit feedback; and said database using feedback to adjust a lesson, and thereby learning more about said user.
4. A system for organizing knowledge in such a way that users can find knowledge, learn from it, and add to it as needed, comprising: a knowledge base comprising knowledge, meta-knowledge that was created at a time of entry of said knowledge, and meta-knowledge in the form of one or more annotations that accumulate over time, said annotations including any of, but not limited to, usefulness of said knowledge, additional user opinions, certifications of veracity of said knowledge, commentary by users, and connections between said knowledge and other units of knowledge; a viewing tool for accessing said knowledge; a tutor for maintaining a model of a user, and for finding useful knowledge to present to said user; an authoring tool for adding knowledge into said knowledge base; and a backend system comprising a database that stores and manages said knowledge base.
15. A system for organizing knowledge in such a way that users can find knowledge, learn from it, and add to it as needed, comprising: a knowledge base comprising knowledge, meta-knowledge that was created at a time of entry of said knowledge, and meta-knowledge in the form of one or more annotations that accumulate over time, said annotations including any of, but not limited to, usefulness of said knowledge, additional user opinions, certifications of veracity of said knowledge, commentary by users, and connections between said knowledge and other units of knowledge; a viewing tool for accessing said knowledge, wherein said viewing tool supports choosing topics that a user wants to learn about, viewing explanations provided to said user as a sequence of presentations, and annotating; a tutor for maintaining a user learning model, and for finding useful knowledge to present to said user; an authoring tool for enabling an author to add knowledge into said knowledge base; and a backend system comprising a database system that stores and manages said knowledge base.
35. An apparatus for storing, organizing, and sharing a very large amount of loosely structured data among a large and diverse group of users, comprising: a database that can be accessed and modified by thousands of users concurrently; a distributed registry for keeping track of where and how said data and associated metadata are stored; wherein data objects are represented as nodes of a labeled graph, and said associated metadata are represented by labeled links connecting said nodes; wherein said nodes represent data of different types and in different formats, including text, image, sound, video, and structured data.
47. A user interface for use with a knowledge base comprising knowledge, meta-knowledge that was created at a time of entry of said knowledge, and meta-knowledge in the form of one or more annotations that accumulate over time, said annotations including any of, but not limited to, usefulness of said knowledge, additional user opinions, certifications of veracity of said knowledge, commentary by users, and connections between said knowledge and other units of knowledge, said user interface comprising: a viewing tool for accessing said knowledge, wherein said viewing tool supports choosing topics that said user wants to learn about, viewing explanations provided to said user as a sequence of presentations, and annotating; said viewing tool further comprising: a module for allowing said user to navigate through links, see patterns in connections, and reorganize information according to multiple navigational schemes; a module for allowing user to see the detailed local information, and also see how that information fits into a broader global context; and a topic search engine for selecting one or more topics that a user wants to learn about.
59. A method for use with a knowledge base comprising knowledge, meta-knowledge that was created at a time of entry of said knowledge, and meta-knowledge in the form of one or more annotations that accumulate over time, said annotations including any of, but not limited to, usefulness of said knowledge, additional user opinions, certifications of veracity of said knowledge, commentary by users, and connections between said knowledge and other units of knowledge, said method comprising the steps of: when a data object is registered, using its type and content to generate a fast, unique hash value, which is used as an index into a registry; wherein said hash value is used to identify and register a data object into said registry and is used as an index in said registry's hash table.
60. A data object registry method for use with a knowledge base comprising knowledge, meta-knowledge that was created at a time of entry of said core content, and meta-knowledge in the form of one or more annotations that accumulate over time, said annotations including any of, but not limited to, usefulness of said knowledge, additional user opinions, certifications of veracity of said knowledge, commentary, and connections between said knowledge and other units of knowledge, said method comprising the steps of: representing a plurality of registered data objects as a hash table entry; wherein hash table entries identify a data object's location, representation, and any associated metadata; each hash table entry comprising an index hash, an optional cryptographically strong signature for verification and security, a data identifier, and a metadata identifier.
Key Drawing(s):
"The Knowledge Web--an Overview
Several of the key concepts underlying the knowledge web's approach to addressing the identified problems are detailed below.
A Broad Knowledge Base
A community of people with knowledge to share put knowledge into a knowledge base using a set of user tools. The knowledge may be in the form of documents or other media, or it may be a descriptor of a book or other physical source.
A central feature of the knowledge web is that each piece of knowledge is associated with various types of meta-knowledge about what the knowledge is for, what form it is in, and so on. Conceptually, the knowledge base is a centralized resource with possible private compartments, much like the Internet. Also like the Internet, it is intended to be implemented in a distributed manner.
The knowledge in the knowledge base may be created specifically for the knowledge base, but it may also consist of information converted from other sources, such as scientific documents, books, journals, Web pages, film, video, audio files, and course notes. As Marshall McLuhan observed, "The content of the new medium is the old medium."
The initial knowledge within the knowledge web comprises existing curriculum materials, books and journals, and those explanatory pages that are already on the World Wide Web. These existing materials already contain enough examples, problems, illustrations, and even lesson plans to provide utility to an early incarnation of the knowledge web.
The knowledge base thus represents:
Knowledge (online content or references to online or offline content), and
Meta-knowledge, created at the time of entry, accumulating over time, and indicating, for example, the usefulness of the knowledge, reflecting user opinions of the knowledge, certifying the veracity of the knowledge, providing commentary on the knowledge, or indicating connections between the knowledge and other units of knowledge.
Collaboration and Community Involvement
One aspect of the knowledge web is peer-to-peer publishing. The task of recording and sharing the world's knowledge is so monumental that peer-to-peer publishing by a very large number of people is the preferred manner in which to accomplish it. One of the reasons why the Web and Internet news groups have enjoyed such runaway success is that they allow people to communicate with each other directly, without intermediaries. This basic human desire to share knowledge is also what drives the creation of the knowledge web.
Many people have specialized knowledge about certain topics, and know how to teach them especially well, but there are few easy ways for them to share that information effectively with a large audience, short of teaching a course, writing a textbook, or developing a television special. With the knowledge web's authoring tools, anyone with knowledge to share can publish short pieces, such as a single explanation of a concept--an effort comparable to creating a Web page. These explanations are the basic building blocks of the knowledge web.
While the knowledge web builds on systems such as the World Wide Web, Internet news groups, libraries, professional societies, books, and refereed journals, it allows an even more generalized form of linking than the World Wide Web. In the knowledge web, the author as well as readers can create annotations. These annotations can then be used for advanced features such as author credits, usage tracking, and commenting, that the Web lacks.
Users are also able to add annotations to explanations connecting them to other content, suggesting improvements, and rating their accuracy, usefulness, and appropriateness. Such feedback enhances the value of the knowledge web, keeps it current and useful, and eventually makes its way back to the original authors, so that they can use it to improve their explanations.
This ability of users to comment, filter, and review the content of the knowledge web solves one of the serious problems with peer-to-peer publishing--that of quality control. While publishers of textbooks and journals provide editing and selection services, the information on the World Wide Web is often irrelevant, badly presented, or just plain wrong (and that's not including the pornography and the propaganda). The knowledge web's peer review infrastructure also leads the way for third-party certification of content, further enhancing the knowledge.
Individualized Learning
The knowledge web allows for learning tailored to an individual learner. This is accomplished through the use of a tutor that customizes a user's learning experience based on a user learning model. The tutor handles the key problem of presenting the right information to the user at the right time. The knowledge web's tutor does not create or transform the knowledge itself, but merely maps a path from what a user already knows to what he needs to learn.
The learning model for an individual user combines a user profile, reflecting information on the current knowledge, needs, capabilities, and preferences of the user, with generalized knowledge about how people learn. The tutor draws upon the learning model and the meta-knowledge stored in the knowledge base to allow learning in a manner most fit for the user. In its simplest form, the tutor follows the explicit instructions of a human teacher on how to teach a certain body of knowledge to a certain type of person.
For example, the tutor may show that a given user has a firm understanding of calculus, a general understanding of Newtonian physics, and is completely mystified by quantum mechanics. The model may also include a much more detailed model of certain topics that are of particular importance to the user. For instance, in the case of a medical practitioner, it knows not only the physician's specialty, but it also knows with which recent discoveries, within that specialty, the physician is already familiar.
Most significantly, the user profile of a user is continually updated, allowing the tutor to become better acquainted with the user over time. It knows what the user already understands and what he is ready to learn. It knows the user's learning style: whether he prefers pictures or stories, examples or abstractions ...."
[Original image modified for size and/or readability]"FIG. 2 shows a database represented as a labeled graph, where data objects 24 are connected by labeled links 22 to each other and to concept nodes 20. For example, a concept node for a particular category 21, contains two subcategories 21a, 21b that are linked via labeled links "belongs-to" and "related-to" with text 25 and picture 27. An entity 23 comprises another concept that is linked via labeled links "refers-to," "picture-of," "associated-with," and "describes" with Web page 26, picture 27, audio clip 28, and data 29."
The knowledge base thus represents:
- Knowledge (online content or references to online or offline content), and
- Meta-knowledge, created at the time of entry, accumulating over time, and indicating, for example, the usefulness of the knowledge, reflecting user opinions of the knowledge, certifying the veracity of the knowledge, providing commentary on the knowledge, or indicating connections between the knowledge and other units of knowledge."
[emphasis added, including bullets]