Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
1998-05-29
2001-01-30
Black, Thomas G. (Department: 2776)
Data processing: database and file management or data structures
Database design
Data structure types
C707S793000, C707S793000
Reexamination Certificate
active
06182067
ABSTRACT:
TECHNICAL FIELD
This invention relates generally to the field of information technology and more particularly to knowledge management. The invention concerns methods and systems whereby users of a database system can be informed of relevant information (including text, graphics, and other information stored in electronic form) and be assisted in the transformation of such information into knowledge.
BACKGROUND OF THE INVENTION
Having passed through the agricultural and industrial revolutions, it is now widely accepted that society has entered a new era, the information revolution. Driven by the development of the microprocessor, this new era is characterized by high growth in service industries, globalisation, and rapid change brought about by constant technological innovation.
It is estimated that tangible assets (capital, buildings etc.) may now account for as little as 10% of an organization's total assets, with the balance attributed to intellectual assets such as knowledge, experience, and people.
Few large corporations live even half as long as a person. By 1983, one third of Fortune 500 companies from 1970 had vanished. There is abundant evidence that many were unable to recognize impending threats, identify the implications, or develop responses. Keeping ahead of competition requires the creation of an external focus along with a capacity to adapt quickly to a changing environment.
Rather than deliver the paperless office, the information revolution has been responsible for many companies drowning in a sea of data at the same time as being starved of knowledge. This is known as “Analysis Paralysis”.
Too much information can be both expensive and difficult to manage. Important information can be easily missed. Too little information can see important opportunities missed, or decisions made based upon incomplete or invalid assumptions.
In the present context, “knowledge” may be defined as “information made actionable”. In other words, knowledge is created from information when the experience and skills of a reader are applied in assessing the content of the information in the light of a particular problem or issue, thereby allowing action to be taken. Knowledge is thus a combination of information and the expertise of the reader in interpreting and applying that information.
A “knowledge worker” is a person who works with information. Most knowledge workers have other defined responsibilities in an organisation, in management, marketing, design, etc. It is the role of the knowledge worker to transform available information into the knowledge needed to make business decisions by using his/her experience and skills to interpret and analyse the information, often consulting with others, before delivering a final judgement.
This process of knowledge creation leads to an increase in the organization's intellectual assets. Sadly, however, such knowledge is often left in the head of the creator where it cannot be easily shared and is easily lost. Interest in capturing this important strategic resource has given rise to a new field of science known as “knowledge management”.
In the present context, the term “knowledge management” is intended to include the processes involved in collecting information and knowledge, creating new knowledge from that material and disseminating that knowledge.
A general objective of the present invention is thus to provide methods and systems for facilitating knowledge management within organizations.
SUMMARY OF THE INVENTION
The present invention provides methods for knowledge management which may be performed within a data processing system.
The methods of the present invention may include several distinct phases which may be implemented in various combinations. The methods may include a profiling phase, including the steps of:
establishing and storing a plurality of knowledge related concepts representing a corresponding plurality of subjects, each concept being defined by a set of associated terms which are searchable within documents held in a database; and
establishing and storing a knowledge related profile representing a knowledge requirement associated with the user, the profile being defined by a group of concepts selected from said plurality of concepts.
The presence in a document of terms associated with a concept suggests that the document may be relevant to the concept. The greater the proportion of the set of associated terms which are located in the document, the higher the probable relevance of the document to the concept.
If a concept is included in the group of selected concepts which define the knowledge profile of the user, this suggests that the document may be relevant to the knowledge requirement of the user. The greater the proportion of the group of selected concepts which are covered by the document, the higher the probable relevance of the document to the knowledge requirement of the user.
Each concept may be associated with one or more dimensions indicating the context in which the concept is typically applied by the user. For example, dimensions may include: companies/organizations, industries, products, locations, topics, time periods, people and miscellaneous. In this way, the knowledge profile for the user may include concepts associated with a number of dimensions. The greater the proportion of those dimensions covered by a document, the higher the probable relevance of the document to the profile and hence to the user requirement. Associating concepts with dimensions may also allow the user to group or sort documents according to those dimensions.
The profiling phase may include the optional steps of a user specifying locations within documents (such as, for example, the title, abstract and/or body) to be searched for terms associated with each concept, and storing the locations as part of the respective concept definition.
Advantageously the profiling phase may allow a user to create a knowledge concept which is a derivative of an existing knowledge concept. The derivative may be a modified version of the existing concept and may be marked as a private concept belonging to the user.
The profiling phase may allow a user to create a knowledge profile which is a derivative of an existing knowledge profile. The derivative may be a modified version of the existing profile and may be marked as a private profile belonging to the user.
Each knowledge profile may be defined by groups of concepts to be used in distinct ways. In one embodiment:
identifier concepts are used to locate relevant documents;
modifier concepts are used to attach increased importance to documents;
classifier concepts are used to sort or categorize documents; and
negator concepts are used to exclude documents.
A subset of, or superset including, these concept groups may alternatively be used.
In one embodiment the step of establishing a knowledge profile may allow a user to:
specify a minimum number of concepts which must be present;
select specific concepts that must be present;
nominate a minimum value that must be reached;
specify a minimum number of dimensions to be present; and/or
select specific dimensions that must be present,
in a document for it to be considered a match.
Further, the step of establishing a knowledge profile preferably allows the user to nominate specific source databases of information from which documents are to be extracted. More preferably, the user may nominate a subset of available information sources.
Further still, the step of establishing a knowledge profile may allow the user to specify criteria by which priority documents are separated from other documents.
The methods of the present invention may include an extraction phase. The extraction phase may be used to extract material from the internet or from other electronic sources, via the engagement of search engines.
The extraction phase may include the steps of:
forming a query string for a knowledge profile as a logical expression of concepts selected during the profiling phase;
converting the query string into a text string containing the set of associ
Presnell Peter Donald
White Michael Anthony
Black Thomas G.
Do Thuy
Knowledge Horizons PTY Ltd.
Oliff & Berridg,e PLC
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