Relational database system containing a multidimensional hierachical model of interrelated subject categories with recognition capabilities

The present invention is a database and a method of producing that database which can be used to determine the meaning of scientific or technical documents, such as patents and/or technical or scientific publications and/or abstracts of these patents or publications, and to assign the technical documents to one or more scientific or technical categories within a multidimensional hierarchical model which reflects the business, scientific or technical interests of a business, scientific or technical entity or specialty.

BACKGROUND OF THE INVENTION 
The present invention is a database. In particular, the present invention 
is multi-dimensional database that models a business or scientific or 
technical body of work. Relational databases are well known and have been 
used to manipulate discrete numerical values. There are many commercial 
databases available which permit the user to build relationships between 
tables and some of these databases allow large text fields to be stored 
and manipulated. 
However, the prior art does not disclose a database system that can: 
1) import and parse complex technical documents containing complex fields; 
2) analyze the technical content of the documents in order to extract the 
meaning and assign these documents to one or more categories within a 
multidimensional hierarchy; 
3) utilize mathematical formula to interrelate the different levels of the 
multidimensional hierarchy and derive higher (more abstract) meanings; 
4) manipulate the parsed fields, the text fields and/or the categorizations 
to produce graphical and spreadsheet-like displays which allow the user to 
readily discern an overall pattern in the intensity of patent and/or 
research activity across a span of years; 
5) manipulate the parsed fields, the text fields and/or the categorizations 
to produce graphical and spreadsheet-like displays which allow the user to 
readily identify trends and discontinuities in the overall pattern in the 
intensity of patent and/or research activity across a span of years; 
6) allow the categorization to be easily verified by displaying the 
technical documents and/or abstracts of those documents and/or patent 
claims within one or more categories to which it was described in 2); 
7) allow engineers or scientists to evaluate the technical details of 
individual patents and/or scientific or technical literature and to 
capture this evaluation into subject-specific tables which capture the 
essence of the document into sortable discrete fields; 
8) link the relational database containing some or all of the above 
capabilities to an electronic source of the full text or abstracts of U.S. 
patents and/or foreign patents and/or foreign patent applications. The 
full text of these patents and/or applications may be stored in a 
database, on a CD-ROM, on a LAN, on a WAN or on the Internet. 
Mathematical methods similar to weighted sum have been used against 
numerical measurements based on physical phenomena to measure 
contributions to gross mechanical properties. An example is a weight 
average of polymer concentrations of a particular molecular weight and 
their contributions to the overall gross physical properties of the 
polymer. 
These methods have not been suggested as a means of capturing the technical 
content of complex documents such as patents or technical documents and 
calculating the contribution of each patent or technical document to an 
abstract scientific or business discipline by taking into account the 
weighting factors which represent the stored cumulative expertise of a 
team of experts in the scientific or business discipline. In particular, 
there has been no suggestion of using this method to identify patterns of 
research efforts as reflected in the patents or technical publications 
obtained by a scientific or business entity. More particularly, there has 
been no suggestion of using such methods to identify trends and 
discontinuities in the overall patterns of research efforts as reflected 
in the patents obtained by a scientific or business entity. These types of 
mathematical relationships are most easily determined by the use of 
electronic databases. 
SUMMARY OF THE INVENTION 
The present invention is a database system and a method of producing that 
database which can be used to assign scientific or technical documents, 
such as patents and/or technical or scientific publications and/or 
abstracts of these patents or publications, to one or more scientific or 
technical categories within a multidimensional hierarchical model which 
reflects the business, scientific or technical interests of a business, 
scientific or technical entity or specialty. Lower level categories which 
reflect scientific concepts and technology may be recognized and assigned 
by use of a set of expert technical searches (ETS). Higher level, more 
abstract, concepts may be recognized and assigned by mathematically 
manipulating the matrix of lower level scientific and technology concepts, 
in combination with a matrix of contributions to higher level concepts, 
which reflects the stored cumulative expertise of a team of technical or 
scientific experts. The population of each category, within the 
multidimensional hierarchy may be used to prepare graphical and/or tabular 
overviews which reflect the research activity within a business or 
technical entity or specialty over a span of years and across an unlimited 
number of dimensions. The graphical and/or tabular overviews allow trends 
and discontinuities to be readily identified. The apparent trends and 
discontinuities may be verified by examining the individual documents 
and/or abstracts and/or patent claims, and/or all associated fields which 
contribute to both the overall trends and any specific trends within a 
business entity or technical specialty. Specific detail on individual 
documents and/or abstracts and/or claims may also be captured in discrete 
fields and linked to the categories within the hierarchical model and the 
technical documents and/or abstracts and/or claims. All of the above data 
may also be linked to full-text sources of the documents.

DESCRIPTION OF THE PREFERRED EMBODIMENT 
The present invention is a database system which contains a hierarchical 
model of a complex business, scientific or technical entity or specialty 
and the associated technical documents, such as patents or scientific or 
technical publications, or abstracts of those patents or publications, 
which reflect each aspect of that model. Each technical document may be 
assigned to one or more categories within the hierarchical model. The 
model and associated technical documents and/or abstracts and/or technical 
indexing may be used to determine trends and discontinuities within the 
bounds of the model and may also be used to project unanticipated trends 
and discontinuities beyond the bounds of the model. The individual 
documents and/or abstracts within one or more categories or subsets of 
categories, may be displayed along with the corresponding U.S. claims 
and/or European granted or application claims by use of a relational 
database which is viewed through a computerized graphical interface. 
This database disaggregates a set of patents and/or technical documents 
into discrete technical categories by use of a set of pre-defined search 
protocols which match the scientific or technical concepts within the 
model. The pre-defined search strategies automatically categorize the set 
of technical documents to fit the multidimensional hierarchical model of a 
scientific or business discipline. The pre-defined search strategies may 
be conducted on a commercial database system and the results of these 
searches stored in a local electronic database. Alternatively, the 
pre-defined search strategies may be conducted in a local electronic 
database containing records captured from a commercial database system or 
by a combination of these two methods. The categorization may then be used 
by the relational database to identify trends and discontinuities in the 
research efforts represented by the technology in the underlying technical 
documents and/or patents. The categorization may also be used to allow the 
technical experts to chill-down and examine the underlying documents 
and/or abstracts and/or claims which contribute to these trends and 
discontinuities. 
The overall goal of this method is to use this model to identify 
unanticipated trends and discontinuities in the pattern of research effort 
in a technical, scientific or business entity or discipline as reflected 
by the technical documents and/or patents obtained by that scientific or 
business entity or discipline, where the overall pattern itself has been 
previously hidden due to both the complexity of the individual documents 
and the large number of documents being considered. In addition, this 
method of analysis may be used to confirm anticipated trends and 
discontinuities in the pattern of research effort in a technical, 
scientific or business entity or discipline as reflected by the technical 
documents and/or patents obtained by that scientific or business entity or 
discipline, where the overall pattern itself has been previously hidden 
due to both the complexity of the individual documents and the large 
number of documents being considered. 
The documents and/or abstracts and/or claims and/or technical indexing may 
be electronically stored in a relational database and linked to the 
categorization which reflects the overall hierarchical model. The 
documents and/or abstracts and/or claims and/or technical indexing may be 
displayed on a computerized graphical interface. All of the documents may 
be displayed or only those documents within one or more categories may be 
displayed or only those documents within a subset of one or more 
categories may be displayed. Subsets of all of the documents and/or 
subsets of one or more of the categories may be selected by further 
searching of any of the stored data. These subsets of documents and/or 
abstracts and/or claims may be displayed on a computerized graphical 
interface. 
The relational database can also contain subject-specific tables of 
technical details such as catalyst precursors, cocatalysts, reaction 
conditions, reactor types, or product characteristics, which are captured 
in a discrete form by scientists evaluating the underlying patents or 
technical documents. 
The relational database can also contain links to full-text sources of 
patents or technical documents either in a database, on a CD-ROM, a local 
LAN, a Wide-Area-LAN or on the Internet. The retrieved full-text patents 
may include the full text of U.S. and/or foreign patents or published 
patent applications and may also include images of the full patents or a 
combination of text and images. The retrieved full text technical 
documents may also include the full text and or images of scientific or 
technical publications. 
The present database can be used to answer a number of questions. The 
database can be used to identify the overall pattern of research activity, 
as reflected in the number of patents or technical documents. The database 
can also be used to identify trends and discontinuities across the 
multidimensional hierarchy which is needed to model complex scientific, 
technical and business disciplines. Specifically this database can pose 
questions such as: 
"What are the interesting areas within the boundaries of this model?" 
"What change has occurred in the area of catalytic cracking?" 
"Where have competitor companies concentrated their research efforts as 
reflected in the number of patent applications or technical publications 
over the past 10 years?" 
"To what areas have competitor companies moved their top researchers?" 
"Which patents have used a particular catalyst in combination with a 
particular cocatalyst with a particular solvent for a polymerization of a 
particular monomer?" 
"Which companies are the top 15 most active in the area of biopolymers and 
what sub-specialties have they processed over the last 10 years?" 
In order to create a computer system which can answer higher level 
questions such as these, the computer system must have a pre-defined model 
of the overall scientific or business discipline and the computer system 
must have already analyzed the technical content of each patent or 
technical document with respect to that model. The system of sophisticated 
technical searches and the method of applying those searches to a set of 
technical documents, such as patents, to categorize those documents to 
match a multidimensional hierarchy which models a scientific or business 
entity or discipline is the subject of this patent memo. 
The relational database can also contain subject-specific tables of 
technical details such as catalyst precursors, cocatalysts, reaction 
conditions, reactor types, product characteristics, which are captured in 
a discrete form by scientists evaluating the underlying patents. The 
original classification serves to group similar patents together. An 
individual scientist or engineer may then evaluate each patent in a 
particular group and capture the essential details of each invention into 
a subject-specific table which can be linked back to the original 
documents and/or abstracts and to the original categorization. The expert 
analysis can also feed back into the categorization of the patents to 
enhance the categorization achievable by sophisticated technical searches. 
FIG. 1 shows a high-level overview of the database design covered by this 
invention, with increasing levels of abstraction. Stage I is the least 
abstract and Stage VI is the most abstract. 
Stages I and II represent well known methods of dealing with collections of 
full-text patents and semi-organized analyses of those collections of 
patents in the form of spreadsheets or small databases. Stage III through 
VI represent the subject of this invention whereby increasingly abstract 
concepts and overviews can be derived from a collection of electronically 
available patent abstracts, and/or technical documents, technical 
indexing, and patent claims. 
Stage I represents the actual patents or technical documents, whether in a 
stack of paper copies or in an electronic collection on a CD-ROM, in a 
database, on a LAN or on the Internet. 
Stage II represents commonly used methods of analyzing full-text patents 
and/or technical documents and storing that patent-by-patent analysis in 
the form of subject-specific spreadsheets, and small databases. An 
enhancement represented by the current invention is that these detailed 
analyses can then be electronically linked to a given patent and/or patent 
family and electronically displayed along with the Patent Abstracts and/or 
Patent Claims and/or technical documents. 
Stages III through VI represent the database design of this invention. 
Stage III represents the electronic capture of Patent Abstracts, and/or 
technical documents and the parsing of the complex, multi-entity data 
fields which usually accompany these Patent Abstracts, such as the Patent 
Inventors, Patent Numbers, Patent Companies (Assignees), Patent Legal 
Status and Patent Priority data. For example, the Parsed Patent Number 
Record would capture a separate record for each patent equivalent 
including the patent number, publication date and patent status. Similar 
levels of detail are captured for each parsed field. Also represented at 
this level is the electronic capture of the U.S. Claims and the European 
Claims (granted patent and published applications) and associated 
information such as inventor and assignee. All of these fields are 
electronically linked and may be electronically displayed as a set of 
information pertinent to one particular patent and/or patent family on a 
computerized graphical interface. Technical Documents may be similarly 
captured and the associated complex fields parsed to yield normalized 
data. 
Stage IV represents the design of a Customized Technical Subject Hierarchy 
which models the specific interests of a business entity or technical or 
scientific specialty and the many facets of that entity or specialty. The 
hierarchical model consists of two or more levels, each level consisting 
of sets of categories which define the concepts being modeled. For 
example, this method models business, scientific, or technical entities 
and/or specialties at two levels in the same sense as a Genus-Species 
relationship. The higher level terms would correspond to a broader, more 
abstract genus and the lower level categories would correspond to a more 
specific set of sub-categories corresponding to the species. A 
multiplicity of levels can be employed to capture complex topics which 
require more than two levels of abstraction. 
This Technical Subject Hierarchy is used to create a set of sophisticated 
expert technical searches (ETS), using the best chemical and technical 
indexing available along with the text of the patent abstracts and/or the 
patent claims and/or the technical document. An expert search is created 
to identify patents or technical documents that are pertinent to each 
individual category within the Customized Technical Subject Hierarchy and 
the results of these searches are electronically stored in tables 
represented by Stage V. The stored results are electronically linked to 
the corresponding patent and/or patent family. Stage IV Automatically 
feeds into Stage V. 
The set of expert searches represented by Stage IV can be automatically 
executed against a new set of patents and/or technical documents. This new 
set of patents and/or technical documents may represent either recently 
published patents or technical documents and/or recently identified 
patents or technical documents and/or older collections of patents or 
technical documents which are now being captured with the methods of this 
invention. 
Stage V represents the stored assignment of each patent to one or more oft 
he categories in the Customized Technical Subject Hierarchy of Stage IV. 
By this approach, each category is populated with records that match the 
search criteria. The automatic execution of expert technical searches 
analyze the indexing, abstract, text and/or claims for each patent and 
assign each patent and/or technical document to one or more categories in 
the Customized Technical Subject Hierarchy of Stage IV. Additionally, 
Stage V includes one or more Fractional Contribution Matrices which may be 
used to derive more abstract concepts from the existing categorization. 
The Fractional Contribution Matrices are created by collecting the 
combined expertise of acknowledged experts in a technical or scientific 
field and representing this expertise in a stored matrix. This Fractional 
Contribution Matrix represents the cumulative expertise of a set of 
technical experts as to how much a lower level scientific or technology 
category will contribute to a higher-level, more abstract concept. 
The database system allows patents and/or technical documents to be 
electronically captured and analyzed at a convenient time. This set of 
analyzed patents and/or technical documents may then be used to identify 
trends and discontinuities in the overall pattern of research efforts 
represented by the set of patents or technical documents. These trends and 
discontinuities may be identified any time following the analysis of the 
set of patents and/or technical documents. The stored analysis may be used 
minutes, days, months or years later. 
Stage V and the Parsed data from Stage III feed into Stage VI. Stage VI 
represents a high-level overview of a business, scientific or technical 
entity or specialty and provides a method for grasping the pattern of 
research effort represented by a collection of patents or technical 
documents. These patterns are obscure at Levels I and II, and can only be 
clearly observed after pursuing the methods of this invention to achieve 
the higher level abstraction represented by Stages III through VI. 
The dashed line from Stage V to Stage I represents the fact that the data 
stored in the database, and all associated analyses of Stages II although 
VI, may be used to identify patents and/or technical documents of 
particular interest for a particular application. The patent numbers for 
this set of patents may then be used as unique identifiers to 
electronically link to full text sources of patents and display the full 
text and associated graphic images of the set of patents. The electronic 
full text sources of these patents may be on a CD-ROM, in a database, a 
LAN or on the Internet. Unique Identifiers may similarly be used to link 
to sources of full-text technical or scientific documents. I. Reducing 
Unstructured Text to Fit a Multidimensional Database 
The unstructured text in technical documents is reduced to fit a 
multidimensional hierarchy which models a complex system of scientific or 
business information, such as that represented by the body of patents 
pertinent to a particular scientific or business discipline. This method 
utilizes sophisticated expert technical searches (ETS) to automatically 
categorize technical documents, such as patents or scientific 
publications. This method disaggregates a set of patents or technical 
documents into discrete technical categories by use of a set of 
pre-defined search protocols to assign each document to one or more 
categories. A complex set of technical and/or scientific search strategies 
may be produced to identify and automatically categorize documents to fit 
a pre-defined matrix of technical categories. The matrix of technical 
categories models a scientific, engineering or business area and may 
consist of hundreds of categories on one or more levels of abstraction. 
Each category has a unique set of characteristic terms associated with it. 
For each category a predefined set of search parameters would be created 
comprised of technical search terms such as 
U.S. Patent Classification 
International Patent Classification 
Technical Indexing Terms 
Chemical Structures 
Chemical Formulas 
Registry Numbers 
Chemical Codes 
Polymer Codes 
Database-Specific Codes and Descriptors 
Title Text 
Abstract Text 
Full Text of original documents and/or patents 
The expert technical and/or scientific searches (ETS) use all the expertise 
of a skilled technical searcher and capture that expertise in a set of 
pre-defined search strategies. These pre-defined search strategies may be 
run against one or more sets of technical documents, such as patents 
assigned to a particular business or scientific entity or in a particular 
technical specialty. The pre-defined search strategies automatically 
categorize the set of technical documents to fit the multidimensional 
hierarchical model of a scientific or business discipline. The pre-defined 
search strategies may be conducted on a commercial database system and the 
results stored in a local electronic database or the pre-defined search 
strategies may be stored and executed in a local electronic database 
containing records captured from a commercial database system. The 
categorization may then be used to identify trends and discontinuities in 
the research efforts represented by the technology in the underlying 
technical documents and/or patents. Furthermore, mathematical 
relationships may be applied against the matrix of technical categories to 
extract hidden details and patterns and to generate additional levels of 
abstraction. 
Example 1 shows the logic for automatically assigning patents to a 
pre-defined subject-specific-hierarchy, using a series of expert technical 
searches (ETS). Similar methods could also be used to automatically 
categorize scientific and/or technical publications. 
EXAMPLE 1 
Automatically Assigning Patents to Categories Within a Hierarchical Model 
of a Business or Technical Specialty 
Create a Subject Hierarchy which models a complex business or technical 
entity For each Subject in the Hierarchy 
Create an expert technical search (ETS) 
Apply the expert technical search against a set of patent data 
For each patent which matches the expert technical search (ETS) criteria 
create a record in a table indicating the subject and the patent's unique 
identifier 
Example 2 shows a portion of a Subject Hierarchy which could be used to 
model a business or technical entity. For each category within the Subject 
Hierarchy, in Example 2, an expert technical search (ETS) would be created 
which would use all the expertise of a skilled information specialist to 
capture patents or technical documents that fit that subject category. 
Note that the hierarchy in Example 2 makes no attempt to categorize all 
Biopolymers, but rather only categorizes those Biopolymers of interest to 
a particular business or technical specialty. 
EXAMPLE 2 
A Partial Hierarchy representing the Interests of a Particular Business or 
Technical Specialty 
______________________________________ 
1000 Biopolymers 
1010 Phosphorus-Modified Biopolymers 
1020 Polyester-type Biopolymers 
1030 Biopolymers as Metal Supports 
______________________________________ 
Example 3 shows two sample expert technical searches (ETS) which could be 
created to identify those patents or technical documents which should be 
assigned to subjects within the Partial Subject Hierarchy of Example 2. 
Example 3 shows the expert technical searches needed to identify patents 
which should be assigned to category 1010 (Phosphorus-Modified 
Biopolymers) and to category 1020 (Polyester-type Biopolymers) within the 
Subject Hierarchy of Example 2. 
EXAMPLE 3 
Expert Technical Searches Created to Achieve Optimum Recall and Specificity 
within the Limits of the Available Indexing System(s) 1010 
Phosphorus-Modified Biopolymers 
______________________________________ 
1010 Phosphorus-Modified Biopolymers 
1: P0599/PI (S) M2460/PI 
2: (2001/KS &gt; 0201/KS) and (C08L-001:/IC or C08L-003:/IC or 
C08L-005:/IC or 1985/KS) 
3: (BIOPOLYMER/LT or CELLULOSE/LT or CELLULOSIC 
RESIN/LT or NATURAL RESIN/LT or POLYSACCHARIDE/LT 
or HYDROXYETHYL CELLULOSE/LT or HYDROXYPROPYL 
CELLULOSE/LT) LINK (PHOSPHORUS ORGANIC/LT or 
PHOSPHORUS CONTAINING ACID/LT) 
1 or 2 or 3 
1020 Polyester-type Biopolymers 
1: /LT biopolymer/p.polyester/p 
2: (1291/KS or C08G-063/06/IC or polyester/p/LT) and 
(*biosynethesis/it or C12P-007/42/IC or C12P-007/62/IC) 
1 or 2 
______________________________________ 
The expert subject searches in Example 3 would be further modified and 
customized to fit the particular needs of a specific hierarchical model. 
For example, the overall database might be focused on oil well drilling 
additives or it might be focused on cosmetic formulations. The searches 
would be further refined to selectively retrieve one set of patents or 
technical documents for a database focused on fluid loss control 
additives, for use in oil well drilling fluid additives, and to 
selectively retrieve a different set of patents or technical documents for 
a database focused on cosmetic formulations. 
II. Multidimensional Tabular and Graphical Display of Data 
In the preceding steps, each patent has been automatically assigned to one 
or more categories within the Subject-Specific-Hierarchy and linked to the 
parent patent record in the relational database. Also in preceding steps, 
the complex, multi-entity data fields have been parsed to multi-field 
tables and linked to the parent patent or technical document record in the 
relational database. Table 3 and FIG. 2 show two of the simplest displays 
possible using these Subject-Categories. 
Table 2 shows a portion of the table which stores the assigned 
Subject-Categories. These are the same Subject-Category), assignments that 
are created by using stored expert technical searches (ETS) to assign 
individual patents or technical documents to the categories within a 
Subject-Specific-Hierarchy. These stored category assignments may be used 
to create a tabular display of the subject-assignments over a span of 
years as shown in Table 3. These categories may also be used to create a 
graphical display of the subject-assignments over a span of years, as 
shown in FIG. 2. 
TABLE 2 
______________________________________ 
Category Year Unique ID 
______________________________________ 
104 Drill Bit Topology 
1982 12345678 
104 Drill Bit Topology 
1984 23456789 
104 Drill Bit Topology 
1985 34567890 
104 Drill Bit Topology 
1986 45678901 
104 Drill Bit Topology 
1986 56789012 
104 Drill Bit Topology 
1986 67890123 
104 Drill Bit Topology 
1987 78901234 
104 Drill Bit Topology 
1987 89012345 
104 Drill Bit Topology 
1987 90123456 
104 Drill Bit Topology 
1987 99123456 
203 Drill Fluid Rheology 
1982 12345678 
203 Drill Fluid Rheology 
1983 78123456 
203 Drill Fluid Rheology 
1983 67123456 
203 Drill Fluid Rheology 
1983 56123434 
203 Drill Fluid Rheology 
1983 45123345 
203 Drill Fluid Rheology 
1984 23456789 
203 Drill Fluid Rheology 
1984 23123435 
______________________________________ 
TABLE 3 
______________________________________ 
Counts of Patents per Category per Year 
Category 1982 1983 1984 1985 1986 1987 
______________________________________ 
104 Drill Bit Topology 
1 1 1 3 4 
203 Drill Fluid Rheology 
1 4 2 3 3 3 
301 Propping Agents 
19 15 4 18 31 51 
320 Acidification Agents 
10 10 17 20 14 7 
350 Fungicides 
15 23 19 11 6 3 
______________________________________ 
There is no limit to the number of dimensions which can be displayed in 
this fashion. More complex tabular displays and graphical displays may be 
created by linking the category populations (i.e. the count of patents 
assigned to each category) to the multi-entity data fields (e.g. patent 
number, patent status, patent publication date, company data, inventor 
data) and creating multidimensional tabular and graphical displays. 
Example 3 shows the logic of creating a display by company, of the top 15 
inventors, by inventor (one inventor per page), by subject-category (one 
subject-Category per line), per year (one count of patents per column) 
with totals accumulating the total number of patents filed by a particular 
inventor in a particular company across a span of years. 
EXAMPLE 3 
______________________________________ 
For each Company 
For a selected set of Subject-Categories 
For a selected range of years 
Identity the 15 Inventors with the highest number of patents 
For the Inventor with the highest number of patents 
Produce a tabular display by Subject Category by Year 
Produce a graphical display by Subject Category by Year 
For the Inventor with the next highest number of patents 
Produce a tabular display by Subject Category by Year 
Produce a graphical display by Subject Category by Year 
For the Inventor with the next highest number of patents 
Produce a tabular display by Subject Category by Year 
Produce a graphical display by Subject Category by Year 
etc. 
______________________________________ 
The inventors may be sorted by the total number of patents filed within a 
selected set of subject-categories, within a selected range of years, 
within a particular company and displayed in a series of tabular and 
graphical displays. As shown in FIG. 3, the first page would display a 
tabular or graphical overview of the number of patents filed by the most 
active inventor, in each category, within company XYZ, over a span of 
years. The next page would display a tabular or graphical overview of the 
number of patents filed by the next most active inventor, in each 
category, within company XYZ, over a span of years and so on for the top 
15 inventors. A display of this type could be used to identify trends and 
discontinuities in the research activity of the most prolific inventors 
within a company. Similar methods could be used to display the activities 
of authors of technical and/or scientific documents. 
III. Multidimensional Hierarchy of Interrelated Subject Categories 
This invention further includes the method of deriving more abstract 
concepts from the set of stored category), assignments, by applying 
mathematical methods to extract these more abstract concepts. These more 
abstract concepts can not be readily identified by the application of 
expert technical searches alone. However, a method of quantifying the 
research effort expended in the areas defined by each of these more 
abstract concepts is of great value. These more abstract concepts can be 
identified by the use of both the matrix of technical and/or scientific 
concepts, identified by the application of expert technical searches, and 
a matrix of stored expert opinion. The matrix of stored expert opinion 
represents the cumulative opinion of a group of expert technical staff 
and/or scientists, on the fractional contribution of each technical and/or 
scientific concept to each of the higher-level, more abstract concepts. 
The present database includes a multidimensional hierarchy of subject 
categories wherein the different levels of the hierarchy are interrelated 
by a mathematical formula. The mathematical formula which interrelates the 
different levels takes the form of a sum of an aggregate count of unique 
items in a category multiplied by weighting factors for each category in 
the next higher (more abstract) level. Each higher (more abstract) level 
of the hierarchy is therefore a weighted sum of contributions from each 
category in the previous level. The aggregate count of unique items is 
arrived by modeling a scientific or business discipline based on the 
technical content of patents and/or technical documents in that scientific 
or business discipline. The weighting factors are derived by the 
cumulative knowledge of experts in that scientific or business discipline 
to reflect the impact of each technical category on the next the higher 
level of the hierarchy. 
EQU f(x1)=sum((attribute-1*weighting-factor-1)+(attribute-2*weighting-factor-1) 
+ . . . ) 
EQU f(x2)=sum((attribute-1*weighting-factor-2)+(attribute-2*weighting-factor-2) 
+ . . . ) 
EQU f(x3)=sum((attribute-1*weighting-factor-3)+(attribute-2*weighting-factor-3) 
+ . . . ) 
In particular, these weighted averages may also be calculated across a span 
of years to reflect a multidimensional representation of research efforts 
across a span of technologies and across a span of years. 
The Higher Level Subject Categories may be derived by matrix manipulation 
of two matrices, one representing the known subject category assignments 
in a hierarchical model of a business or technical specialty, and the 
other matrix, representing the cumulative knowledge of technical experts 
in a given business or technical entity or specialty. Table 4 shows a two 
dimensional matrix which represents the number of patents assigned to 
selected subject categories across a selected span of years. Table 4 may 
represent the patents filed by an entire company, or the patents filed in 
a particular business enterprise, or the patents filed by a particular 
inventor within a particular company or business enterprise, as examples. 
TABLE 4 
______________________________________ 
Counts of Patents per Category per Year 
Category 1982 1983 1984 1985 1986 1987 
______________________________________ 
104 Drill Bit Topology 
1 0 1 1 3 4 
203 Drill Fluid Rheology 
1 4 2 3 3 3 
301 Propping Agents 
19 15 4 18 31 51 
320 Acidification Agents 
10 10 17 20 14 7 
350 Fungicides 
15 23 19 11 6 3 
______________________________________ 
Table 5 represents the cumulative knowledge of a group of technical experts 
in a given business or technical entity. For example, Table 5 may 
represent the collective opinion of a group of technical experts on the 
contribution of a patent in Drill Bit Topology to a series of higher level 
concepts. For example the cumulative knowledge may say that a single 
patent in Drill Bit Topology would contribute 0.22 patent-units toward a 
theoretical patent in Drill Bit Deposition, 0.24 patent-units toward a 
theoretical patent in Drill Bit Corrosion, and 0.27 patent-units toward a 
theoretical patent in Formation Penetration. 
TABLE 5 
__________________________________________________________________________ 
Fractional Contribution Matrix of Each Category to a Higher-Level 
Concept 
Environ. 
Environ. 
A Drill Bit 
Drill Bit 
Formation 
Formation 
Impact of 
Impact of 
Category Deposition 
Corrosion 
Penetration 
Stability 
Fluid 
Trailings 
__________________________________________________________________________ 
104 Drill Bit Topology 
0.22 0.24 0.27 0.11 0.07 0.09 
203 Drill Fluid Rheology 
0.33 0.12 0.19 0.02 0.23 0.11 
301 Propping Agents 
0.09 0.07 0.22 0.5 0.05 0.07 
320 Acidification Agents 
0.12 0.33 0.19 0.06 0.22 0.08 
350 Fungicides 
0.05 0.04 0.21 0.06 0.32 0.32 
__________________________________________________________________________ 
Table 6 represents the summation of the matrix multiplication of these two 
matrices leading to the estimate of the number of theoretical patents in 
these higher level subjects. For example, the number of theoretical 
patents in Drill Bit Deposition would be derived by multiplying column A, 
which represents the cumulative opinion of a group of technical experts 
(Table 5), by the number of patents in each category for each year (Table 
4) and summing the contribution of each category to the theoretical number 
of patents in Drill Bit Deposition. Table 6 displays the derived count of 
patents in each of these higher-level, more abstract concepts, across a 
span of years. 
TABLE 6 
______________________________________ 
Theoretical Count of Patents in a Higher-Level Concept 
Category 1982 1983 1984 1985 1986 1987 
______________________________________ 
Drill Bit Deposition 
4.21 5.02 4.23 5.78 6.42 7.45 
Drill Bit Corrosion 
5.59 5.75 7.13 8.9 8.11 7.32 
Formation Penetration 
9.69 10.79 8.75 10.91 
12.12 
14.83 
Formation Stability 
11.13 9.56 4.31 11.03 
17.09 
26.6 
Environ. Impact of Fluid 
8.25 11.23 10.55 9.58 7.45 6.02 
Environ. Impact of 
7.13 9.65 8.03 6.8 5.81 5.78 
Trailings 
______________________________________ 
Table 7 represents the calculation of the theoretical number of patents in 
Drill Bit Deposition which would be represented by a set of patents. For 
each subject category from Table 4, the number of patents would be 
multiplied by the fractional contribution of that subject category, from 
Table 5, Drill Bit Deposition in year 1982. The theoretical number of 
patents contributed by each category would be summed to arrive at a 
theoretical number of patents in Drill Bit Deposition in 1982. 
TABLE 7 
______________________________________ 
Sample Calculation of Drill Bit Deposition Patents in 1982 
Fractional 
Theoretical 
Category 1982 Contribution 
Number of Patents 
______________________________________ 
104 Drill Bit Topology 
1 0.22 0.22 
203 Drill Fluid Rheology 
1 0.33 0.33 
301 Propping Agents 
19 0.09 1.71 
320 Acidification Agents 
10 0.12 1.2 
350 Fungicides 
15 0.05 0.75 
4.21 
______________________________________ 
FIG. 4 displays the data from Table 6 in a graphical display which allows 
the trends and discontinuities in the research patterns, represented by 
the count of theoretical patents, in the higher-level, more abstract 
subjects in Table 6, to be observed. These trends and discontinuities were 
previously hidden due to both the complexity and length of each patent 
and/or technical document in the set of documents under review, and also 
due to the complexity of the higher level concepts themselves. These 
higher level concepts can not be searched by use of an expert technical 
search (ETS) but rather must be derived from lower level concepts which 
can be searched using an expert technical search (ETS), using the methods 
of this invention.