Node Attributes

[JarbasAI]

every node as a section of arbitrary data, and the current achitecture allows "crawlers" to easily answer questions of the type "is this and example of that?" and makes it also possible to ask "how related it this to that?" by measuring node distance we get a confidence

but when actually consuming data there will be more kinds of questions:

• what does Node produce?
• what can be created from node?
• what does Node need to exist?

this is not info very easy to get from just connections, how would you relate milk to cow? they are related but milk doesn't make sense to be a child of cow (its not an example of a cow)

the solution could be NodeTypes, each type would have some data by definition, and nodes could be of several type, john would be of the type animal and human

what types should be there available? what questions are relevant to each type?

in the data of an animal node we could have: { name: cow creates: milk needs: oxygen eats: food provides: meat and clothes cousins: related nodes with no directly defined relationship, crawlers can check here where to "jump" depending on the question }

mycroft can now answer "where does milk come from?" by checking type of milk ("animal product") and then crawling nodes of the type animal and checking the data field of "provides" would answer all animals that produce milk

what types should come by default? how to decide a convention to make it easy for both humans and machines?

---

the current aproach is the following, node types will be discussed somewhere else with a different purpose #14

Node:
       name:
       type: "informational"   <- all discussed nodes so far are informational
       Connections:
           synonims: []  <- is the same as
           antonims: [] <- can never be related to
           parents: []  <- is an instance of
           childs: [] <- can have the following instances 
           cousins: [] <- somewhat related subjects 
           spawns: []  <- what comes from this?
           spawned_by: [] <- where does this come from?
           consumes: [] <- what does this need/spend ?
           consumed_by: []  <- what consumes this?
           parts : [ ] <- what smaller nodes can this be divided into?
           part_off: [ ] <- what can be made out of this?
       Data:
            description: wikidata description_field
            abstract: dbpedia abstract
            summary: wikipedia_summary
            pics: [ wikipedia pic, dbpedia pic ]
            infobox: {wikipedia infobox}
            wikidata: {wikidata_dict}
            props: [wikidata_properties] <- if we can parse this appropriatly we can make connections
            links: [ wikipedia link, dbpedia link  ]
            external_links[ suggested links from dbpedia]

[JarbasAI]

now that we have a few backends, i think nodes will be populated like this

keeping in mind #14 all nodes discussed are type "informational"

dbpedia backend:

    Node:
       name: node name
       parents: [ dbpedia types]
       childs:
       synonims:
       antonims:
       cousins: [ dbpedia_related_subjects, dbpedia_see_also]
       Attributes:
            abstract: dbpedia abstract
            links: [ dbpedia link ]
            pics: [ dbpedia pic ]
            external_links[ suggested links from dbpedia]

wikipedia backend:

    Node:
       name: node name
       parents: []
       childs:
       synonims:
       antonims:
       cousins: []
       Attributes:
            summary: wikipedia_summary
            links: [ wikipedia link ]
            pics: [ wikipedia pic ]
            infobox: {wikipedia infobox}

wikidata backend:

# parse properties for connections

    Node:
       name: node name
       parents: [ what_field, instance_field ]
       childs:
       synonims:
       antonims:
       cousins:
       Attributes:
            description: wikidata description_field
            data: {wikidata_dict}
            props: [wikidata_properties]

wikihow backend:

doesnt populate nodes, answers how questions

user backend:

# confirms data, provides all fields
# can add any arbitrary field to attribs
# following fields are always checked for depending on crawl strategy, other fields are info to be retrieved to user

    Node:
       name:
       type: "informational"   #all discussed nodes so far are informational
       parents: # is an instance of
       childs: # can have the following instances
       synonims: # is the same as
       antonims: # is opposite to
       cousins: # related subjects
       Attributes:
           spawns: []  <- what comes from this?
           spawned_by: [] <- where does this come from?
           consumes: [] <- what does this need/spend ?
           consumed_by: []  <- what consumes this?
           parts : [ ] <- what smaller nodes can this be divided into?
           part_off: [ ] <- what can be made out of this?

[JarbasAI]

I would refactor a node as this:

Node:
       name:
       type: "informational"   <- all discussed nodes so far are informational
       Connections:
           synonims: []  <- is the same as
           antonims: [] <- can never be related to
           parents: []  <- is an instance of
           childs: [] <- can have the following instances 
           cousins: [] <- somewhat related subjects 
           spawns: []  <- what comes from this?
           spawned_by: [] <- where does this come from?
           consumes: [] <- what does this need/spend ?
           consumed_by: []  <- what consumes this?
           parts : [ ] <- what smaller nodes can this be divided into?
           part_off: [ ] <- what can be made out of this?
       Data:
            description: wikidata description_field
            abstract: dbpedia abstract
            summary: wikipedia_summary
            pics: [ wikipedia pic, dbpedia pic ]
            infobox: {wikipedia infobox}
            wikidata: {wikidata_dict}
            props: [wikidata_properties] <- if we can parse this appropriatly we can make connections
            links: [ wikipedia link, dbpedia link  ]
            external_links[ suggested links from dbpedia]