Knowledgeable machines and applications
The present invention discloses methods, systems, and tools to extract the usable knowledge from a body of knowledge and build computer/machine useable data structures stored in one or more non-transitory storage media. The body of knowledge is regarded as a composition of ontological subjects (OSs) of different orders. Using the participation information of the OSs into each other, one or more association strength matrices and/or conditional occurrence probability matrices and/or ontological subject maps are built from which the value significance, information content, and type and strength of the relationship of the partitions (i.e. OSs of different orders) of the composition are calculated and learned. The methods systematically build one or more data structures carrying the actionable knowledge from a body of knowledge and enables one to build knowledgeable and context aware systems and machines for various desired applications. Exemplary systems and machines, for implementing the methods and some exemplary applications and services, are disclosed.
1. A knowledgeable system comprising:
one or more data processing devices or computing devices, communicatively or operatively coupled to, one or more non-transitory computer readable storage media, configured to provide:
one or more data structures, corresponding to participations of ontological subjects of predefined orders, of one or more universes, into each other, and is built by executing a set of computer executable instructions comprising:
instructions to access a collection of content forming the one or more universes;
instructions for partitioning the collection of content to one or more pluralities of partitions, wherein at least one plurality of partitions is assigned with a predefined ontological subject order,
obtaining ontological subjects of at least one predefined order, instructions for building one or more data structures corresponding to least one participation pattern of the ontological subjects of predefined order, k into the partitions of said order l, which can be denoted by PM k|l ,
one or more data structures corresponding to association strengths between the ontological subjects of the said one or more universes, wherein the association strength data structure, denoted by ASM k|l , is calculated by processing the said data structures corresponding to least one participation pattern,
one or more data structures corresponding to conditional occurrence probabilities of said ontological subjects, wherein the conditional occurrence probabilities, which can be denoted by COP k|l , wherein the entries are given by:
cop
k
|
l
(
i
❘
"\[LeftBracketingBar]"
j
)
=
iop
i
k
❘
"\[LeftBracketingBar]"
l
·
asm
j
i
k
❘
"\[LeftBracketingBar]"
l
∑
q
iop
q
k
❘
"\[LeftBracketingBar]"
l
·
asm
q
i
k
❘
"\[LeftBracketingBar]"
l
wherein the cop k|l (i|j) is the conditional occurrence probability of ontological subject of ith of order k given the occurrence of ontological subject of jth of order k in a partition or ontological subject of order l, wherein iop i k|l and iop q k|l are the independent probability of occurrences of ontological subject of ith, a qth, of order k, respectively, and asm ji k|l are the individual entries of said data structure ASM k|l ;
accessing a client request comprising input content;
identifying a context or a universe corresponding to said client request;
using said one or more data processing devices or computing devices to generate a data structure corresponding to one or more composing routes or maps by processing at least one of said data structures corresponding to said participations of ontological subjects of different order into each other, said association strengths, and said conditional occurrence probabilities;
and
output one or more composition of ontological subjects by processing the client's request and one or more of, said one or more composing routes or maps, said data structures corresponding to at least one of said participations, said association strengths, and said conditional occurrence probabilities.
2. The knowledgeable system of claim 1 further comprising access to one or more data structures corresponding to ontological subject map of one or more universes.
3. The knowledgeable system of claim 1 , wherein said association strengths of the ontological subjects is a function of number of co-occurrences, in one or more partitions of the compositions, of at least a pair of the ontological subjects and the number of occurrences, in one or more partitions of the compositions, of at least one of the ontological subjects of the pair, wherein said calculated value is an indicative of association strength of the pair of ontological subjects and are represented by one or more data structures.
4. The system of claim 1 , further comprising one or more data structures corresponding to information value significance of first type conditional entropy measure which can be denoted by H2 i k|l and is given by:
H
1
i
k
|
l
=
-
∑
j
iop
j
k
|
l
·
cop
k
|
l
(
i
❘
"\[LeftBracketingBar]"
j
)
log
2
(
cop
k
|
l
(
i
❘
"\[LeftBracketingBar]"
j
)
)
,
i
,
j
=
1
…
N
wherein H1 i k|l is the first type conditional entropy of ith ontological subject of order k, the cop k|l (i|j) is the conditional occurrence probability of ontological subject of ith of order k given the occurrence of ontological subject of jth of order k in a partition or order l, wherein iop j k|l is the independent probability of occurrences of jth ontological subject of order k, in the partitions or ontological subjects of order l.
5. The system of claim 1 , further comprising one or more information value of second type Conditional Entropy Measure” which can be denoted by H2 i k|l and is given by:
H 2 i k|l =−iop i k|l Σ j cop k|l ( j|i )log 2 ( cop k|l ( j|i )), i,j= 1 . . . N
wherein H2 i k|l is the second type conditional entropy of ith ontological subject of order k, the cop k|l (j|i) is the conditional occurrence probability of ontological subject of jth of order k given the occurrence of ontological subject of ith of order k in a partition or ontological subject of order l, wherein iop i k|l is the independent probability of occurrences of ith ontological subject of order k, in the partitions or ontological subjects of order l.
6. The system of claim 1 , wherein said collection of content further comprises the client input content and/or a collection of content that is assembled in response to the client input.
7. A method of facilitating a service by a knowledgeable system for a client over a computer network, comprising:
providing an access for the client over the network, said network carries, transmit, or transport data at least at the rate of 10 million bits per second (Mbps)
receiving an input from the client, said input cause to identify the network address of a provider of said service;
exchanging signals or data between the client and provider of said service, wherein said service is performed by at least one computer program executed by one or more data processing device or computing devices, wherein said one or more data processing device or computing devices having at least a singular or compound processing speed of 1 gigahertz (Ghz), to process a composition and provides one or more of:
one or more data structures, corresponding to participations of ontological subjects of predefined orders, of one or more universes, into each other, and is built by executing a set of computer executable instructions comprising:
instructions to access a collection of content forming the one or more universes;
instructions for partitioning the collection of content to one or more pluralities of partitions, wherein at least one plurality of partitions is assigned with a predefined ontological subject order, l,
obtaining ontological subjects of at least one predefined order, k,
instructions for building one or more data structures corresponding to least one the participation pattern of ontological subjects of predefined order, into the partitions of said order l, which can be denoted by PM k|l ,
one or more data structures corresponding to association strengths between the ontological subjects of the said one or more universes, wherein the association strength data structure, which can be denoted by ASM k|l , is calculated by processing the said data structures corresponding to least one participation pattern,
one or more data structures corresponding to conditional occurrence probabilities of said ontological subjects, wherein the conditional occurrence probabilities, COP k|l , wherein the entries are given by are given by:
cop
k
|
l
(
i
❘
"\[LeftBracketingBar]"
j
)
=
iop
i
k
❘
"\[LeftBracketingBar]"
l
·
asm
j
i
k
❘
"\[LeftBracketingBar]"
l
∑
q
iop
q
k
|
l
·
asm
q
i
k
|
l
wherein the cop k|l (i|j) is the conditional occurrence probability of ontological subject of ith of order k given the occurrence of ontological subject of jth of order k in a partition or ontological subject of order l, wherein iop i k|l and iop q k|l are the independent probability of occurrences of ontological subject of ith, a qth, of order k, respectively, and asm ji k|l are the individual entries of said data structure ASM k|l ;
one or more data structures corresponding to value significances of the ontological subjects of the compositions,
access a client comprising input content;
identifying a context or a universe corresponding to said client request;
using said one or more data processing devices or computing devices generating a data structure corresponding to one or more composing routes or maps by processing at least one of said data structures corresponding to said participations of ontological subjects of different order into each other and said value significances of oncological subjects of the composition;
composing a response content by processing the client request and one or more of, said one or more composing routes or maps, said data structures corresponding to at least one of said participations and said value significances of oncological subjects of the composition; and
transmitting the response content back to the provider of the service or the client.
8. The method of claim 7 , wherein said client is a computer program having instructions executable by a computer system over the network, said computer system comprising a computer-readable storage medium and at least one data processing device, capable of executing the instructions of at least one computer program embedded thereon.
9. The method of claim 7 , wherein provider of the service is at least one computer program having instructions executable by a computer system over the network, said computer system comprising a computer-readable storage medium and one or more data processing or computing devices, capable of executing the instructions of at least one computer program embedded thereon.
10. The method of claim 7 , further comprising: providing one or more data structure corresponding to the association strengths of the ontological subjects of the composition.
11. The method of claim 10 , further comprising: providing one or more data structures, corresponding to visually displayable graph or network of graphical objects, whose data values are calculated as a function of said association strengths of the ontological subjects of the composition.
12. The method of claim 7 , further comprising: providing one or more data structure corresponding to the association strengths of the ontological subjects of the composition having different predefined ontological subject order.
13. The method of claim 7 , wherein one of said value significances first type Conditional Entropy Measure which can be denoted by H2 i k|l and is given by:
H
1
i
k
❘
l
=
-
∑
j
iop
j
k
❘
l
·
cop
k
❘
l
(
i
❘
"\[LeftBracketingBar]"
j
)
log
2
(
cop
k
❘
l
(
i
❘
"\[LeftBracketingBar]"
j
)
)
,
i
,
j
=
1
…
N
wherein H1 i k|l is the first type conditional entropy of ith ontological subject of order k, the cop k|l (i|j) is the conditional occurrence probability of ontological subject of ith of order k given the occurrence of ontological subject of jth of order k in a partition or ontological subject of order l, wherein iop j k|l is the independent probability of occurrences of jth ontological subject of order k, in the partitions or ontological subjects of order l.
14. The method of claim 7 , wherein one of said value significances second type Conditional Entropy Measure” which can be denoted by H2 i k|l and is given by:
H 2 i k|l =−iop i k|l Σ j cop k|l ( j|i )log 2 ( cop k|l ( j|i )), i,j= 1 . . . N
wherein H2 i k|l is the second type conditional entropy of ith ontological subject of order k, the cop k|l (j|i) is the conditional occurrence probability of ontological subject of jth of order k given the occurrence of ontological subject of ith of order k in a partition or ontological subject of order l, wherein iop i k|l is the independent probability of occurrences of ith ontological subject of order k, in the partitions or ontological subjects of order l.