THE WELCH COMPANY
440 Davis Court #1602
San Francisco, CA 94111-2496
415 781 5700
rodwelch@pacbell.net


S U M M A R Y


DIARY: March 25, 1996 08:03 AM Monday; Rod Welch

Continue review Landauer's paper on Plato's Problem.

1...Summary/Objective
2...Derived Constraints from Core Genetic Based Method
3...Keyword Retrieval Subject Identification Classification Categories
4...Information Retrieval
5...Convert Information into Knowledge
6...Dimension Matching Uses Triangulation to Measure Accuracy of Knowledge
7...Complexity, Induction and Guessing
8...Hilly Terrain Causes Errors of Induction
9...Dimension matching in LSA, discussed initially in the record on 960321
10...Time Impact on Knowledge Conversion
11...Brain & Nurobiology
12...Chunking Accomplished by Power of Mind's Parallel Processing


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CONTACTS 

SUBJECTS
Catagorization, Subjects
Vocabulary Learning Rates
Pre-literate Language Growth
Genetic Knowledge; Pinker
SDS Subject Indexing Procedures, Key Words
Catagorization
Subjects Too Many Overwhelm Span of
Key Word Catagorization
Keyword Retrieval

1311 -
1311 -    ..
1312 - Summary/Objective
1313 -
131301 - Follow up ref SDS 19 8566.
131302 -
131303 - Pre-school children learn words at the rate of 7 - 10 words per day,
131304 - ref OF 6 line 312, ref OF 6 line 1031, ref OF 6 line 1076.
131306 -  ..
131307 - The capacity of pre-literate children to acquire vocabulary points to
131308 - innate genetic strictures on the structure of relations among concept
131309 - classes to associate words (sounds) with objects and differentiate
131310 - words based observable differences in the associated objects,
131311 - ref OF 6 line 326.
131313 -  ..
131314 - Modern theories of knowledge acquisition suppose the existence of
131315 - genetic constraints that facilitate induction. ref OF 6 line 338
131317 -  ..
131318 - Pinker proposes 15 different genetic constraints. ref OF 6 line 375.
131319 -        ..
131320 -        It is not clear if this is to be construed as reflecting
131321 -        the idea that humans are born with some "knowledge" per
131322 -        Newsweek article at ref SDS 14 line 77.
131324 -      ..
131325 -     Landauer and Damias feel the prospect of evolution creating such
131326 -     constraints is remote, which seems to support their idea of
131327 -     "derived" constraints based on a process or method of induction,
131328 -     per below.
131330 -      ..
131331 -     It is not clear why, if the brain is complex, its processes cannot
131332 -     also be complex.  Hands, elbows work one way, feet, knees work
131333 -     similarly but differently for different functions.  Eyes are
131334 -     different from nose, and from the rib cage.  So the prospect that
131335 -     different mental processes (constraints) could have evolved as
131336 -     innate structures, is not terribly unattractive, implausible.
131338 -  ..
131339 - Children may assume for example in learning language that there is a
131340 - different word for a different object, ref OF 6 line 363.
131341 -
131343 -  ..
131344 - Derived Constraints from Core Genetic Based Method
131345 -
131346 - Landauer and Damias consider the idea that there may a single or very
131347 - few natural constraints, proposed by Shepard, that evolve in the brain
131348 - into complex forms or sets of derived constraints based on human
131349 - experience, i.e., we grow our knowledge of constraints on interpreting
131350 - language which in turn supports interperting conduct and the larger
131351 - world.  ref OF 6 line 382.
131352 -
131353 -    This reflects current thinking that mental capacity is a
131354 -    combination of nature and nurture, such that the environment can
131355 -    enhance natural talents, per Newsweek article ref SDS 14 line 79.
131356 -
131357 -
131358 -
131359 -
131360 -
1314 -

SUBJECTS
Retrieval Methods/Rules
Artificial Intelligence Information Management (IT)
Reports, Details Linked to Summary
Retrieval; Automation, Implementing, 930119
Controlled Visibility Subjects, Automated MBO Organic Subject Structure
Categories Classification Organization Based on Objectives
Objectives Provide Methodology of Organic Structure
Keyword Retrieval Different from Organic Subject Structures Subject I

3510 -
351101 -  ..
351102 - Keyword Retrieval Subject Identification Classification Categories
351103 -
351104 - Follow up ref SDS 19 8566.
351105 -
351106 - Review of Landauer's paper yesterday about how the mind categorizes
351107 - things shows the enormous challenge of information retrieval using
351108 - keyword methods, ref SDS 19 8566, and cites research on 910418 showing
351109 - that managing subjects is a very complex task. ref SDS 4 5584  On
351110 - 891117 problems with keyword retrieval occurred on project to review
351111 - claims on Santa Clara Jail project. ref SDS 2 0005
351113 -  ..
351114 - Adults recognize there can be many different words for the same
351115 - object, ref OF 6 04FT, reflecting analysis on 960324 in the record,
351116 - ref SDS 19 8566, and earlier on 890523. ref SDS 1 SQ5L
351117 -
351118 -         [On 960415 see example. ref SDS 20 5922]
351120 -      ..
351121 -     Adults also recognize that putting several words together creates
351122 -     more uniqueness, i.e., simply expand the pattern.  This reflects
351123 -     the process of expanding root words with more syllables, and again
351124 -     seems to reflect the organic structure of the brain that is
351125 -     applied in the SDS for managing subjects explained on 890523.
351126 -     ref SDS 1 SQ5L
351127 -
351128 -         [On 960406 example of adults having trouble on the job finding
351129 -         information on a computer. ref SDS 20 5922  Keyword methods
351130 -         have not been effective. ref SDS 20 0253
351132 -          ..
351133 -         [On 990526 SDS organic structues more effective than keywords
351134 -         for information retrieval. ref SDS 31 0977
351136 -          ..
351137 -         [On 990329 Steve Pinker's book "How the Mind Works" explains
351138 -         the number of alternate ways to say the same thing is very
351139 -         large which makes key words problematic as an organizing
351140 -         methodology for finding things. ref SDS 30 GP2S
351142 -      ..
351143 -     The childish brain may make simple assumptions of differentiation.
351144 -     Experience in the world gives the brain wider patterns to match.
351145 -     The authors (Landauer and Damias) consider this idea on page 10.
351146 -     ref OF 6 03BN
351147 -
351149 -  ..
351150 - Information Retrieval
351151 -
351152 - Methods to improve information retrieval using LSA mathematical
351153 - modeling steps are described on page 19. ref OF 6 07VE
351154 -
351155 -    I don't understand the matrix processing described in the paper.
351156 -    ref OF 6 08QG
351158 -     ..
351159 -    We need an example to illustrate the explanation on page 20.
351160 -    ref OF 6 08SF
351162 -  ..
351163 - Retrieval is treated in SDS primarily as part of Subject Indexing and
351164 - somewhat through reports, per work on 930326. ref SDS 5 3345  Typical
351165 - SDS challenge is explained on 940824, at ref SDS 8 1411; more recent
351166 - work is on 950626, ref SDS 11 2772, discussed with Hank Hatch on
351167 - 960410. ref SDS 22 0400
351168 -
351169 -         [On 990526 SDS organic structues more effective than keywords
351170 -         for information retrieval. ref SDS 31 0977
351172 -  ..
351173 - I wonder if this method was explained in Landauer's book "The Trouble
351174 - with Computers" per review on 950710. ref SDS 12 0003.  The book does
351175 - say that "spatial filing" using icons was found by testing not to be
351176 - effective method of retrieval, ref SDS 12 1773, which seems to
351177 - conflict with Intel's ideas for applying computers to support
351178 - management reported on 960507, ref SDS 23 1111, and on 960509.
351179 - ref SDS 24 3502
351180 -
351181 -
351182 -
351183 -
351184 -
351185 -
3512 -

SUBJECTS
Knowledge v. Information
Induction Bridges Gap between Information
Convert Information into Knowledge
Process Information, Knowledge
Information, Convert into Knowledge
Continual Learning
Communication Metrics
Distinct from Data, Information, Wisdom

4410 -
441101 -  ..
441102 - Convert Information into Knowledge
441103 -
441104 - Follow up ref SDS 19 8566.
441105 -
441106 - The paper specifically describes converting information into
441107 - knowledge, ref OF 6 08QG, which is analysed at ref SDS 25 0881.
441108 - ref SDS 25 0550.
441110 -  ..
441111 - Equally important, the paper recognizes the role of "experience" in
441112 - the knowledge process. ref OF 6 7331 and ref OF 6 13EW
441114 -  ..
441115 - This seems to correct initial impression that converting information
441116 - into knowledge is not discussed, reported in the record on 960229.
441117 - ref SDS 15 0980
441118 -
441119 -      [On 960518 support for Welch "Management Cycle." ref SDS 25 8811]
441121 -  ..
441122 - It supports the idea in the NWO paper at ref OF 4 line 514, and the
441123 - explanation of Communication Metrics on 950327, ref SDS 10 3279 and
441124 - ref SDS 10 8008.  Landauer's paper seems to reflects the scenario in
441125 - the POIMS paper at ref OF 3 line 200.
441127 -      ..
441128 -     Seems to support analysis of Drucker's work that distinguishes
441129 -     getting more information from achieving effective communication,
441130 -     on 931130, ref SDS 6 5567; and, the analysis of Kerzner lecture on
441131 -     950202. ref SDS 9 8446
441133 -      ..
441134 -     May relate to the explanation of "Turning Water into Wine" in Time
441135 -     magazine reviewed on 960409. ref SDS 21 7211
441137 -  ..
441138 - Communication Metrics says the process of making the conversion is the
441139 - Welch Management Method:  plan, perform, report, that results in a
441140 - continuous stream of case studies, explained in more detail on 950830.
441141 - ref SDS 13 0096
441143 -  ..
441144 - "Knowledge" seems to be described as a process again at ref OF 6 line
441145 - 778, possibly by combining and condensing "local information."
441147 -  ..
441148 - Knowledge is described as a process of creating connections
441149 - using existing units of memory to create new ones, ref OF 6 line 1773.
441150 -
441151 -
441152 -
4412 -

SUBJECTS
Dimension Matching
Latent Semantic Analysis (LSA)
Examples showing Induction is Occurring
Errors of Induction, Measuring Understanding
Errors, cause, Drifting Off Course, Complexity

5207 -
520801 -  ..
520802 - Dimension Matching Uses Triangulation to Measure Accuracy of Knowledge
520803 -
520804 - Follow up work at ref SDS 19 8599.
520805 -
520806 - The authors explain a process of mental metrics that use dimension
520807 - matching, ref OF 6 05E2, to make connections based on triangulation
520808 - ref OF 6 6020, that converts information into knowledge, per above,
520809 - ref SDS 0 5689, using statistical weights roughly described as
520810 - guessing to determine the best fit, per analysis on 960324.
520811 - ref SDS 19 0083
520813 -  ..
520814 - The process is summarized near the end of the paper. ref OF 6 5063,
520815 -
520816 -    This may be the "processing" that Jeromy Campbell says occurs in
520817 -    the subconscious mind, in his book "The Improbable Machine"
520818 -    reviewed on 900303. ref SDS 3 0405
520819 -
520820 -       [On 960518 authors define "meaning space." ref SDS 25 4939]
520822 -        ..
520823 -       [On 960809 more research on "meaning space." ref SDS 26 7860]
520825 -  ..
520826 - Complexity, Induction and Guessing
520827 - Hilly Terrain Causes Errors of Induction
520828 -
520829 - The reason for error from induction using dimension matching is
520830 - explained by example of estimating distances over hilly terrain, see
520831 - ref OF 6 6020, and ref OF 6 7388, and noting the correct choice of
520832 - dimensionality is important to success.  Too few or too many factors
520833 - skews results.  This seems like a way of describing "complexity."
520834 - ref OF 6 8444
520836 -        ..
520837 -       This causes understanding to "drift off course," creating a need
520838 -       for communication "metrics" to maintain alignment.
520840 -        ..
520841 -       Dimension matching that adjusts "meaning" as a function of
520842 -       additional input is inherently prone to error --
520843 -
520844 -          [On 960518 authors define "meaning drift" ref SDS 25 3734]
520845 -
520846 -
520848 -  ..
520849 - Dimension matching in LSA, discussed initially in the record on 960321
520850 - ref SDS 17 5873, and further on 960324, ref SDS 19 8599, is applied to
520851 - "learning" the meaning of words as "semantic" construction at
520852 - ref OF 6 2774, as follows...
520853 -
520854 -        Let us now construe the semantic similarity between two words
520855 -        as a distance: the closer the distance the greater the
520856 -        similarity. Suppose we also assume that the likelihood of two
520857 -        words appearing in the same window of discourse-a phrase, a
520858 -        sentence, a paragraph, or what have you-is inversely
520859 -        proportional to their semantic distance, that is directly
520860 -        proportional to their semantic similarity. We can then estimate
520861 -        the relative similarity of any pair of words by observing the
520862 -        relative frequency of their joint occurrence in such windows.
520864 -    ..
520865 -   This seems essentially to be "guessing" per the record on 960324.
520866 -   ref SDS 19 0083.]
520867 -
520868 -   ...I am not sure what "semantic similarity" means.  Semantic seems
520869 -   to be another word for "meaning", so this seems to be saying we can
520870 -   judge two words to have the same meaning if they occur in the same
520871 -   sentence or paragraph, i.e., window of discourse.  It would be
520872 -   helpful to get an example.
520873 -
520874 -   ...I do not grasp the notion that two words being near in proximity
520875 -   warrants a conclusion of similar meaning.  Off-hand, that is not the
520876 -   ordinary experience.  We do encounter words positioned similarly
520877 -   relative to other words in different sentences/paragraphs, and can
520878 -   guess they have similar meanings.
520880 -  ..
520881 - LSA assumptions about the meaning of two words based on co-occurrance
520882 - in small subsamples of language, are at ref OF 6 6111.
520884 -  ..
520885 - The mathematics is discussed in the record on 960321. ref SDS 17 3830
520887 -  ..
520888 - Need for large bodies of text is at ref OF 6 7471 and ref OF 6 5063
520889 -
520890 -
520891 -
5209 -

SUBJECTS
Time Impact on Learning/Knowledge
Fragility of Knowledge, Fades
Maintain Shared Meaning/Knowledge
Information Flows Too Fast
Truth is a Moving Target
1 Minute Align Understanding from
Not Enough Time to Succeed
Information Highway Causes Misktakes, Lack

6710 -
671101 -  ..
671102 - Time Impact on Knowledge Conversion
671103 -
671104 - Follow up ref SDS 17 1234.
671105 -
671106 - Time seems to be factored into the model as a constraint on holding
671107 - awareness of information to dimension match against, ref OF 6 7388,
671108 - and so seems to address concerns in analysis of the paper on 960321.
671109 - ref SDS 17 0076
671110 -
671111 -     [On 960518 review author's explanation about the role of
671112 -     experience (time) in acquiring knowledge. ref SDS 25 8811]
671114 -      ..
671115 -     [On 970707 U.S. Air Force Institute of Technology paper reports
671116 -     study information entropy occurs over time that increases project
671117 -     cost and completion time growth, ref SDS 27 0108.]
671119 -      ..
671120 -     [On 970811 article in "Science" on role of "time" in human memory,
671121 -     ref SDS 28 8899.]
671123 -      ..
671124 -     [On 970829 text book on management describing limited span of
671125 -     attention. ref SDS 29 7721]
671127 -  ..
671128 - One aspect of the time factor is to consider the effect of reading
671129 - text as a continuous stream, rather than blocks as occurs on a page.
671130 - The mind can review to reinforce understanding of a page, but if the
671131 - text comes and goes on a long, continuous line, this would be much
671132 - more difficult.  That is why speech can wander off course and people
671133 - can make incorrect assumptions.
671135 -  ..
671136 - Explanation of creating new knowledge by using existing knowledge, per
671137 - ref OF 6 line 1760, may reflect the time/information correlation in
671138 - POIMS of the management cycle of plan, perform, report, also called
671139 - investing intellectual capital.
671141 -  ..
671142 - Time is further considered at ref OF 6 line 1827:
671143 -
671144 -     But because each node will tend to reactivate ones similar
671145 -     to it, and node vectors of longer durations will come to represent
671146 -     more related components, local hierarchies and partial orders will
671147 -     be statistically common. One aspect of this hypothetical process
671148 -     is a mechanism for the creation of unitary "chunks," vectors
671149 -     representing associations and meanings of arbitrarily large scope
671150 -     and content, the unitization process to which we referred above.
671152 -    ..
671153 -   It has not been apparent to me that vectors represented "durations"
671154 -   which suggests the factor of time, rather my sense has been that
671155 -   "vectors" represent the similarity of usage based on positioning of
671156 -   words relative to other words.
671157 -
671158 -
671159 -
671160 -
6712 -

SUBJECTS
Human Memory, Brain
Brain, Biology
Chunks of Memory

7105 -
710601 -  ..
710602 - Brain & Nurobiology
710603 -
710604 - Explanation of how various parts of the brain's biology might
710605 - accomplish the matrix analysis of LSA set out at ref SDS 17 line 511,
710606 - is explained at ref OF 6 line 913.
710607 -
710608 -     [On 970811 article in "Science" on role of "time" in human memory,
710609 -     ref SDS 28 8899]
710611 -  ..
710612 - Reference to how a "real brain" functions is at ref OF 6 line 1760.
710613 -
710614 -     [On 960518 the mind "grows" knowledge. ref SDS 25 0550]
710616 -  ..
710617 - Suppose the naive mind (brain) constantly generates new temporal
710618 - context vectors to record passing episodes of experience. We may think
710619 - of such vectors as akin to new nodes in a semantic or neural network,
710620 - in that they represent their input and output as weights on a set of
710621 - elements or connections, ref OF 6 line 1774
710623 -       ..
710624 -      Seems to support notion that brain makes connections in a
710625 -      knowledge space comnprised of the vectors.
710626 -
710627 -
710628 -
710630 -  ..
710631 - Chunking Accomplished by Power of Mind's Parallel Processing
710632 -
710633 - Authors explain the mind organizes blocks of data or information the
710634 - brain store and/or associates as related "chunks." ref OF 6 6839 and
710635 - ref OF 6 2NC6
710637 -  ..
710638 - Brain's billions of parallel computational elements instantly resolve
710639 - word usage ambiguity based on context. ref OF 6 24AB
710640 -
710641 -      Aligns with Campbell's book that describes parallel processing
710642 -      occurs in the subconscious, while the conscious span of attention
710643 -      generally operates sequentially to fit the model of real world
710644 -      experience in doing one thing at a time. ref SDS 3 0405
710645 -
710646 -
710647 -
710648 -
710649 -
710650 -
710651 -
710652 -
710653 -
710654 -
7107 -