Computer implemented method for the automated analysis or use of data
There is provided a computer implemented method for the automated analysis or use of data, comprising the steps of: (a) storing in a non-transitory storage medium a structured, machine-readable representation of data that conforms to a machine-readable processable language, in which the structured, machine-readable representation of data includes reasoning passages, wherein the reasoning passages are represented in the processable language to represent semantics of reasoning steps; (b) automatically processing the structured, machine-readable representation of data, including processing at least some of the reasoning passages represented in the processable language to represent semantics of reasoning steps, to reason and to generate an explanation of the reasoning, and (c) storing a result of the reasoning and the explanation of the reasoning.
1 . A computer implemented method for the automated analysis or use of data, comprising the steps of:
(a) storing or accessing in a non-transitory storage medium a structured, machine-readable representation of data that conforms to a machine-readable processable language, in which the structured, machine-readable representation of data that conforms to the machine-readable processable language comprises semantic nodes and passages; and in which each semantic node represents an entity and is itself represented by an identifier; and each passage is either (i) a semantic node or (ii) a combination of semantic nodes; and where machine-readable meaning comes from choice of semantic nodes and a way they are combined and ordered as passages;
in which the structured, machine-readable representation of data includes factual statements, query statements, reasoning statements and reasoning passages;
in which the machine-readable representation of data uses a shared syntax that applies to semantic nodes and passages that represent the factual statements, the query statements, the reasoning statements and the reasoning passages, wherein the syntax is an unambiguous syntax comprising nesting of structured, machine-readable representations of data to a depth;
in which the structured, machine-readable representation of data includes reasoning passages, wherein the reasoning passages are represented in the processable language to represent semantics of reasoning steps;
(b) automatically processing the structured, machine-readable representation of data, including processing at least some of the reasoning passages represented in the processable language to represent semantics of reasoning steps, to reason and to generate an explanation of the reasoning in the processable language, and
(c) storing a final answer of the reasoning and the explanation of the reasoning, in the processable language.
2 . The method of claim 1 where the structured, machine-readable representation of data includes a single syntactical item to disambiguate the meaning of the structured, machine-readable representation of data, in which the single syntactical item to disambiguate meaning is parentheses or brackets.
3 . The method of claim 1 where the structured, machine-readable representation of data includes a single syntactical item to disambiguate the meaning of the structured, machine-readable representation of data, in which the single syntactical item to disambiguate meaning is the only syntactical item to disambiguate the meaning of different combinations of structured, machine-readable representation of data.
4 . The method of claim 1 where the structured, machine-readable representation of data includes a single syntactical item to disambiguate the meaning of the structured, machine-readable representation of data, in which the single syntactical item to disambiguate the meaning of different combinations of structured, machine-readable representation of data is the primary syntactical item to disambiguate the meaning of the combination.
5 . The method of claim 1 where the structured, machine-readable representation of data includes a single syntactical item to disambiguate the meaning of the structured, machine-readable representation of data, in which the single syntactical item to disambiguate meaning represents nesting of the structured, machine-readable representation of data.
6 . The method of claim 1 where the structured, machine-readable representation of data includes a single syntactical item to disambiguate the meaning of the structured, machine-readable representation of data, in which the single syntactical item to disambiguate meaning represents nesting of semantic nodes and passages.
7 . The method of claim 1 where the structured, machine-readable representation of data includes a single syntactical item to disambiguate the meaning of the structured, machine-readable representation of data, in which the single syntactical item to disambiguate meaning represents nesting of semantic nodes and passages to any arbitrary depth.
8 . The method of claim 1 where the structured, machine-readable representation of data includes a single syntactical item to disambiguate the meaning of the structured, machine-readable representation of data, in which the single syntactical item to disambiguate meaning requires that semantic nodes and passages can only be combined in nested combinations.
9 . The method of claim 1 where the structured, machine-readable representation of data includes a single syntactical item to disambiguate the meaning of the structured, machine-readable representation of data, in which the single syntactical item to disambiguate meaning allows for expressions to be nested indefinitely to allow a user to define a concept, coupled with contextual information about the concept, as a hierarchy of semantic nodes.
10 . The method of claim 1 where the structured, machine-readable representation of data includes a single syntactical item to disambiguate the meaning of the structured, machine-readable representation of data, in which the single syntactical item to disambiguate meaning allows for a combination of semantic nodes to contain any finite number of semantic nodes and the semantic nodes within them can also be combination nodes creating any level of nesting.
11 . The method of claim 1 in which a semantic link between nodes, such as ISA, is itself a semantic node.
12 . The method of claim 1 in which the syntax for the machine-readable processable language applies to combinations of semantic nodes that represent factual statements, query statements and reasoning statements.
13 . The method of claim 1 in which the syntax of the structured, machine-readable representation of data conforms to the production grammar “<passage>::=<id>|<passage>::=(<passage><passage>*)” where “<passage>*” means zero or one or more further passages and where <id> is an identifier for a semantic node.
14 . The method of claim 1 in which the machine-readable processable language is a universal language for which any subject matter expressible in natural language is expressible as a structured, machine-readable representation of data or a combination of structured, machine-readable representations of data.
15 . The method of claim 14 in which a structured, machine-readable representation of data represents a specific entity, such as a word, or concept, and once generated, identifies uniquely that specific word, or concept, in the universal language.
16 . The method of claim 1 in which an ordered or partially ordered collection of structured, machine-readable representations of data captures a specific meaning or semantic content.
17 . The method of claim 1 in which the meaning of a structured, machine-readable representation of data comes from statements written in the machine-readable processable language.
18 . The method of claim 1 in which the meaning of a structured, machine-readable representation of data comes from other structured, machine-readable representations of data that represents things that have been said about the structured, machine-readable representation of data.
19 . The method of claim 1 in which a structured, machine-readable representation of data that represents an entity encodes the semantic meaning of that entity through links to structured, machine-readable representations of data of related words, concepts, other terms, or logical processes.
20 . The method of claim 1 in which combining structured, machine-readable representations of data generates a new word, concept, or other term with a new meaning or semantic content in the machine-readable processable language.
21 . The method of claim 1 in which the machine-readable processable language is understandable to human users where it corresponds to an equivalent statement in natural language.
22 . The method of claim 1 in which a semantic node is a structured, machine-readable representation of data that, once defined, has an identifier or ID so it can be referred to within the machine-readable processable language, and the identifier is selected from an address space that is sufficiently large to enable users to select a new identifier with negligible risk of selecting a previously allocated identifier, such as a 128-bit version 4 Universally Unique Identifier (UUID) (RFC 4122) with hyphenated lower-case syntax, or a string, such as a Unicode string.
23 . The method of claim 1 in which the method includes the step of providing a service operable to receive a description of an entity and return one or more identifiers for structured, machine-readable representations of data corresponding to the entity, so that a user is able to use a shared identifier for the entity.
24 . The method of claim 23 in which the service probabilistically compares the description of the proposed semantic node or passages with available information about existing entities to determine if there is a match and returns a new identifier if no match is found.
25 . The method of claim 1 in which the machine-readable processable language is scalable since any natural language word, or concept, can be represented by a structured, machine-readable representation of data.
26 . The method of claim 1 in which the machine-readable processable language is scalable since there are no restrictions on which users can create a structured, machine-readable representation of data or related identifier.
27 . The method of claim 1 , including making a sequence of logical reasoning steps in order to match skills or experience of a candidate with a requirement in a job specification.
28 . The method of claim 1 , including fetching and execution of one or more initial reasoning passages to return other passages with unknowns that need to be processed; processing the unknowns, and the results of processing the unknowns is a tree of connection that is used to give results for the one or more initial reasoning passages.
29 . Computer-based system configured to analyse data, the computer-based system being configured to:
(a) store or access in a non-transitory storage medium a structured, machine-readable representation of data that conforms to a machine-readable processable language, in which the structured, machine-readable representation of data that conforms to the machine-readable processable language comprises semantic nodes and passages; and in which each semantic node represents an entity and is itself represented by an identifier; and each passage is either (i) a semantic node or (ii) a combination of semantic nodes; and where machine-readable meaning comes from choice of semantic nodes and a way they are combined and ordered as passages;
in which the structured, machine-readable representation of data includes factual statements, query statements, reasoning statements and reasoning passages;
in which the machine-readable representation of data uses a shared syntax that applies to semantic nodes and passages that represent the factual statements, the query statements, the reasoning statements and the reasoning passages, wherein the syntax is an unambiguous syntax comprising nesting of structured, machine-readable representations of data to a depth;
in which the structured, machine-readable representation of data includes reasoning passages, wherein the reasoning passages are represented in the processable language to represent semantics of reasoning steps;
(b) automatically process the structured, machine-readable representation of data, including processing at least some of the reasoning passages represented in the processable language to represent semantics of reasoning steps, to reason and to generate an explanation of the reasoning in the processable language, and
(c) store a final answer of the reasoning and the explanation of the reasoning, in the processable language.