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1960s

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1960 Quine

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1961 Lewis

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1962 Austin

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1962 Black

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1962 Kent

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The fundamental problem of information retrieval is that of identifying material that has been stored earlier which is relevant or approximately relevant to a current requirement. The significant aspect of the problem is that the relevant material must be selected from a set of possibly relevant materials. The system must be designed to operate for each possible selection, not just those which will actually be chosen, since this is unknown at the time of design of the system.[1]

The problem of designing an information-retrieval system would be a trivial one (a) if each event impinging on the consciousness of any human beings would result in identical streams of observations, (b) if each observer would use the identical words in identical configurations to describe each such event, and (c) if each person interested in learning of the event would phrase questions using identical terminology.

However, each individual has his own paradigms, or ways of perceiving nature. If there were no common paradigms among individuals, then no system of analyzing, processing, and organizing information would be useful, and a random organization of materials in an information-retrieval system would be all that would be useful. But some paradigms are common to some groups of individuals, otherwise no communication of nay kind would be possible. It is in an attempt to take advantage of common paradigms, to the maximum extent possible, that words, language, and meaning are considered in information-retrieval systems.

Words, language, meaning, ... are basic to all discussion of information retrieval, whether specifically mechanized or not. We must recall that the purpose of information-retrieval systems is to facilitate the communication of information. Various systems effect this communication by by various "signals" -- oral, visual, electronic, etc. -- designed to leap the barriers of space, time, and language. But the information which is the object of all searches is typically contained in graphic records, and these records are typically expressed in words.[2]

These words are usually arranged in such a way as to produce natural language. Pictures or other graphic records which are not made up of words and language are often described in terms of words and natural language. Perhaps this is the reason why systems for "retrieving" graphic records have depended on language-based clues. These consist of words recorded in various ways, as in "open" language, in standardized language, or in codes. It is not surprising that words and language are used to describe or express clues selected by the exercise of recall memory or recognition memory. The higher forms of communication among humans are traditionally -- we might almost say necessarily -- based on words and language.

But is the communication required to achieve effective retrieval the same as the speech and writing by means of which we conventionally communicate our thought? Let us remember that the basic purpose of a retrieval system is to assist in finding desired graphic records. Communication, then, is not an end in itself, but may be one of the means exploited in order to facilitate the finding process. Therefore, everything true for communication systems is not necessarily true for retrieval systems.


From Words, Language, and Meaning in Retrieval Systems (pp. 203-4)

Before the late 1970s, this may have remained the only thesis that took seriously the question of meaning as the basis of information retrieval.

In the information field, there are two diametric paradigms: one essentially views information as meaning or idea, namely idealism, whereas the other as thing or material, namely materialism. These may be illustrated as follows:

Idealists
Materialists

In the U.S., idealism is relatively rich in the West Coast, especially San Fransico Bay Area, CA, whereas materialism in the East Coast, especially Cambridge, MA. It is no accident that UC Berkeley and Silicon Valley prefer idealism, say, HCI to materialism, say, full automation.

1962 Kuhn

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1962 Leavis

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1962 Piaget

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1962 Sellars

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1962 Vygotsky

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1963 Popper

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What we should do, I suggest, is to give up the idea of ultimate sources of knowledge, and admit that all knowledge is human; that it is mixed with our errors, our prejudices, our dreams, and our hopes; that all we can do is to grope for truth even though it be beyond our reach. We may admit that our groping is often inspired, but we must be on our guard against the belief, however deeply felt, that our inspiration carries any authority, divine or otherwise. If we thus admit that there is no authority beyond the reach of criticism to be found within the whole province of our knowledge, however far it may have penetrated into the unknown, then we can retain, without danger, the idea that truth is beyond human authority. And we must retain it. For without this idea there can be no objective standards of inquiry; no criticism of our conjectures; no groping for the unknown; no quest for knowledge.

From On The Sources of Knowledge and of Ignorance (p. 30)

1964 Einbinder

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1964 McLuhan

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1966 Berger

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1966 Foucault

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1967 Bono

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1967 Koestler

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1967 Miller

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1967 Polanyi

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1968 Piaget

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1968 Roszak

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1969 Blumer

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1969 Nida

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Notes

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  1. After C. E. Shannon and W. Weaver, The Mathematical Theory of Communication. The University of Illinois Press, Urbana, 1949.
  2. Graphic ... 3.a of handwriting; used or expressed in handwriting. b. written, inscribed, or recorded in letters, etc." Webster's New World Dictionary of the American Language, college ed., World Publishing Co., Cleveland and New York, c. 1959.
  3. This title is likely to suggest such a machine that may think as well "as we may think," hence the strong AI!
  4. Shannon was V. Bush's student at MIT.