OverviewFilesCommitsIssuesDocsReleasesPeers

opencog-evidence commits / 2158b68

software example
2158b686abaa1c9b43c2b2235c9cd178c5a8eb57
by Linas Vepštas <linasvepstas@gmail.com> · 2025-04-16T21:49:03.000Z

Changed files (1) +42 -6

README.md +42 -6
……@@ -43,12 +43,12 @@ Genealogy, as practiced by familysearch.org (controlled by the Church
4343of the LDS) is semi-automated. The raw material consists of public data
4444about births, deaths, census records, military draft records,
4545naturalization records, passenger lists, parish church records,
46obituaries and the like. Each data item provides a bit of information
47that attests a specific event. Some are highly structured: birth
48certificates have a regular form. Others, not so much: obituaries may or
49may not list relatives, and may or may not make the relationships clear.
50The task is to stitch together a genealogical structure out of these
51fragmentary jigsaw pieces.
46marriage certificates, obituaries and the like. Each data item provides
47a bit of information that attests a specific event. Some are highly
48structured: birth certificates have a regular form. Others, not so much:
49obituaries may or may not list relatives, and may or may not make the
50relationships clear. The task is to stitch together a genealogical
51structure out of these fragmentary jigsaw pieces.
5252
5353The evidentiary issue is that no single attestation of an event or
5454relation is fully trustworthy. A short survey is worthwhile.
……@@ -73,6 +73,42 @@ the record and make a judgement call: is this an appropriate match? If
7373so, it can be added to a record, buttressing support for a particular
7474name, date, location, spelling, event.
7575
76The judgement call is often hierarchical in nature. For example: do the
77father's and mother's names match? Well, perhaps they do, but there is
78some alteration in spelling: Maria vs. Mary, Elizabeth vs. Betty. One
79can assign some probability or confidence in the beleif that these are
80the same parents. To butress that beleif, one can look at sibilings: if
81two children are born three months apart to the same mother, then
82this is a piece of negative evidence that absolutely demands a rejection
83of a match. That is, of course, only if the recorded birthday is
84correct. Perhaps there are other attestations to the birthday? The
85evidentiary chain is now four levels deep: individual -> parents ->
86siblings -> birthdays -> evidence of birthdays. Each arrow in this chain
87can be assigned a confidence; each act of confidence assignment is some
88agglomeration of the supporting evidence. A preponderance of evidence
89is desired. This can be taken as a mathematical mean or average, but
90it can also be some more complex algorithm extending across the
91structure: for example, "voting in new members to the club of facts".
92In comp sci, similarity is measured with cosine distance, Jaquard
93distance, mutual information, Kullbeck-Liebler divergence or any one
94of dozens or hundres of different similarity measures, which can be
95aggregated and weighted in a large variety of ways (random forests,
96collections of experts, membership clubs, etc.)
97
98A much simpler, and more easily automated example occurs in operating
99system storage integrity. Here, one is presented with mutiple files,
100often having the same name, but not always; often having the same
101timestamp, but not always; often appearing in the same directory, but
102not always; often having the same size, but not always; often having the
103same content, but sometimes haveing all-zeros where the data should have
104been. Or perhaps MP3's with missng bytes, or images with steganographic
105watermarks. The challenge is to find the copy of the file that is least
106likely to be corrupted, and is most likely to be "correct". Despite the
107fact that all data is directly available from the operating system,
108using very pure and well-defineed, structured software interfaces, this
109turns out to be a hard problem.
110
111
76112
77113Status
78114------