Search (16 results, page 1 of 1)

0.015885301 = product of:
  0.0953118 = sum of:
    0.0953118 = sum of:
      0.063288145 = weight(_text_:theory in 2051) [ClassicSimilarity], result of:
        0.063288145 = score(doc=2051,freq=4.0), product of:
          0.16234003 = queryWeight, product of:
            4.1583924 = idf(docFreq=1878, maxDocs=44218)
            0.03903913 = queryNorm
          0.3898493 = fieldWeight in 2051, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            4.1583924 = idf(docFreq=1878, maxDocs=44218)
            0.046875 = fieldNorm(doc=2051)
      0.032023653 = weight(_text_:29 in 2051) [ClassicSimilarity], result of:
        0.032023653 = score(doc=2051,freq=2.0), product of:
          0.13732746 = queryWeight, product of:
            3.5176873 = idf(docFreq=3565, maxDocs=44218)
            0.03903913 = queryNorm
          0.23319192 = fieldWeight in 2051, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5176873 = idf(docFreq=3565, maxDocs=44218)
            0.046875 = fieldNorm(doc=2051)
  0.16666667 = coord(1/6)

Abstract

Using Bertram Brookes fundamental equation, sets out a method for calculating the information content of an information process. The knowledge structure variables in the Brookes' equation are operationalized, following principles set out in Claude Shannon's mathematical theory of communication. The set of 'a priori' alternatives and the 'a priori' probabilities assigned to each member of the set by the person undergoing the information process is the operational definition of the variable K(S) from the fundamental equation, which represented the person's knowledge structure before the information process takes place. The set of the a posteriori alternatives and the revised probabilities assigned to each member of the set by the person undergoing the information process is the operational definition of the Brookes variable which is the person's knowledge structure after the information process take place. Gives an example of an information process from a recent archeological discovery

Date

21. 9.1998 9:29:48

0.009134857 = product of:
  0.054809142 = sum of:
    0.054809142 = product of:
      0.109618284 = sum of:
        0.109618284 = weight(_text_:theory in 4985) [ClassicSimilarity], result of:
          0.109618284 = score(doc=4985,freq=12.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.6752388 = fieldWeight in 4985, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.046875 = fieldNorm(doc=4985)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Content

Inhalt: The importance of information need -- The history of information need -- The framework for our discussion -- Modeling the user in information search -- Information seeking's conceptualization of information need during information search -- Information use -- Adaptation : internal information flows and knowledge generation -- A theory of information need -- How information need works -- The user's situation in the pre-focus search -- The situation of user's information need in pre-focus information search -- The selection concept -- A review of the user's pre-focus information search -- How information need works in a focusing search -- Circles 1 to 5 : how information need works -- Corroborating research -- Applying information need -- The astrolabe : an information system for stage 3 information exploration -- Conclusion.

LCSH

Knowledge, Theory of
Information theory

Subject

Knowledge, Theory of
Information theory

0.006949122 = product of:
  0.04169473 = sum of:
    0.04169473 = product of:
      0.08338946 = sum of:
        0.08338946 = weight(_text_:theory in 4474) [ClassicSimilarity], result of:
          0.08338946 = score(doc=4474,freq=10.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.5136716 = fieldWeight in 4474, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4474)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Abstract

This article proposes a theory of information need for information retrieval (IR). Information need traditionally denotes the start state for someone seeking information, which includes information search using an IR system. There are two perspectives on information need. The dominant, computer science perspective is that the user needs to find an answer to a well-defined question which is easy for the user to formulate into a query to the system. Ironically, information science's best known model of information need (Taylor, 1968) deems it to be a "black box"-unknowable and nonspecifiable by the user in a query to the information system. Information science has instead devoted itself to studying eight adjacent or surrogate concepts (information seeking, search and use; problem, problematic situation and task; sense making and evolutionary adaptation/information foraging). Based on an analysis of these eight adjacent/surrogate concepts, we create six testable propositions for a theory of information need. The central assumption of the theory is that while computer science sees IR as an information- or answer-finding system, focused on the user finding an answer, an information science or user-oriented theory of information need envisages a knowledge formulation/acquisition system.

0.0053372756 = product of:
  0.032023653 = sum of:
    0.032023653 = product of:
      0.06404731 = sum of:
        0.06404731 = weight(_text_:29 in 6432) [ClassicSimilarity], result of:
          0.06404731 = score(doc=6432,freq=2.0), product of:
            0.13732746 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03903913 = queryNorm
            0.46638384 = fieldWeight in 6432, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.09375 = fieldNorm(doc=6432)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Date

11. 8.2001 14:48:29

0.00439501 = product of:
  0.02637006 = sum of:
    0.02637006 = product of:
      0.05274012 = sum of:
        0.05274012 = weight(_text_:theory in 5161) [ClassicSimilarity], result of:
          0.05274012 = score(doc=5161,freq=4.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.3248744 = fieldWeight in 5161, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5161)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Abstract

With new interactive technology, information science can use its traditional information focus to increase user satisfaction by designing information retrieval systems (IRSs) that inform the user about her task, and help the user get the task done, while the user is on-line interacting with the system. By doing so, the system enables the user to perform the task for which the information is being sought. In previous articles, we modeled the information flow and coding operations of a user who has just received an informative IRS message, dividing the user's processing of the IRS message into three subsystem levels. In this article, we use Kintsch's proposition-based construction-integration theory of discourse comprehension to further detail the user coding operations that occur in each of the three subsystems. Our enabling devices are designed to facilitate a specific coding operation in a specific subsystem. In this article, we describe an IRS device made up of two separate parts that enable the user's (1) decoding and (2) encoding of an IRS message in the Comprehension subsystem

0.00439501 = product of:
  0.02637006 = sum of:
    0.02637006 = product of:
      0.05274012 = sum of:
        0.05274012 = weight(_text_:theory in 4915) [ClassicSimilarity], result of:
          0.05274012 = score(doc=4915,freq=4.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.3248744 = fieldWeight in 4915, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4915)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Abstract

For millennia humans have sought, organized, and used information as they learned and evolved patterns of human information behaviors to resolve their human problems and survive. However, despite the current focus an living in an "information age," we have a limited evolutionary understanding of human information behavior. In this article the authors examine the current three interdisciplinary approaches to conceptualizing how humans have sought information including (a) the everyday life information seeking-sense-making approach, (b) the information foraging approach, and (c) the problem-solution perspective an information seeking approach. In addition, due to the lack of clarity regarding the rote of information use in information behavior, a fourth information approach is provided based an a theory of information use. The use theory proposed starts from an evolutionary psychology notion that humans are able to adapt to their environment and survive because of our modular cognitive architecture. Finally, the authors begin the process of conceptualizing these diverse approaches, and the various aspects or elements of these approaches, within an integrated model with consideration of information use. An initial integrated model of these different approaches with information use is proposed.

0.0043508383 = product of:
  0.026105028 = sum of:
    0.026105028 = product of:
      0.052210055 = sum of:
        0.052210055 = weight(_text_:theory in 4069) [ClassicSimilarity], result of:
          0.052210055 = score(doc=4069,freq=2.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.32160926 = fieldWeight in 4069, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4069)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Abstract

Shannon's theory of communication is discussed from the point of view of his concept of uncertainty. It is suggested that there are two information concepts in Shannon, two different uncertainties, and at least two different entropy concepts. Information science focuses on the uncertainty associated with the transmission of the signal rather than the uncertainty associated with the selection of a message from a set of possible messages. The author believes the latter information concept, which is from the sender's point of view, has more to say to information science about what information is than the former, which is from the receiver's point of view and is mainly concerned with 'noise' reduction

0.0043508383 = product of:
  0.026105028 = sum of:
    0.026105028 = product of:
      0.052210055 = sum of:
        0.052210055 = weight(_text_:theory in 7747) [ClassicSimilarity], result of:
          0.052210055 = score(doc=7747,freq=2.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.32160926 = fieldWeight in 7747, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.0546875 = fieldNorm(doc=7747)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Abstract

We discuss information by attempting to operationalize it using: (1) Dervin and Nilan's idea that information is a subjective construct rather than an objective thing; (2) Brookes's idea that information is that which modifies knowledge structure; and (3) Neisser's idea that perception is top-down or schemata driven to the point of paradoxon. De Mey, Minsky's theorem of frames, and top-down and bottom-up models from reading theory are discussed. We conclude that information must be rare because only rare information can modify knowledge structure at its upper levels, and that to modify knowledge structure at its upper levels (its essence) information may have to enter the perception cycle in 2 stages

0.0041694725 = product of:
  0.025016835 = sum of:
    0.025016835 = product of:
      0.05003367 = sum of:
        0.05003367 = weight(_text_:theory in 480) [ClassicSimilarity], result of:
          0.05003367 = score(doc=480,freq=10.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.30820292 = fieldWeight in 480, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.0234375 = fieldNorm(doc=480)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Footnote

Weitere Rez. unter: https://crl.acrl.org/index.php/crl/article/view/17830/19659: "Author Charles Cole's understanding of human consciousness is built foundationally upon the work of evolutionary psychologist Merlin Donald, who visualized the development of human cognition in four phases, with three transitions. According to Donald's Theory of Mind, preceding types of cognition do not cease to exist after human cognition transitions to a new phase, but exist as four layers within the modern consciousness. Cole's narrative in the first part of the book recounts Donald's model of human cognition, categorizing episodic, mimetic, mythic, and theoretic phases of cognition. The second half of the book sets up a particular situation of consciousness using the frame theory of Marvin Minsky, uses Meno's paradox (how can we come to know that which we don't already know?) in a critique of framing as Minsky conceived it, and presents group and national level framing and shows their inherent danger in allowing information avoidance and sanctioning immoral actions. Cole concludes with a solution of information need being sparked or triggered that takes the human consciousness out of a closed information loop, driving the consciousness to seek new information.
Cole's reliance upon Donald's Theory of Mind is limiting; it represents a major weakness of the book. Donald's Theory of Mind has been an influential model in evolutionary psychology, appearing in his 1991 book Origins of the Modern Mind: Three Stages in the Evolution of Culture and Cognition (Harvard University Press). Donald's approach is a top-down, conceptual model that explicates what makes the human mind different and exceptional from other animal intelligences. However, there are other alternative, useful, science-based models of animal and human cognition that begin with a bottom-up approach to understanding the building blocks of cognition shared in common by humans and other "intelligent" animals. For example, in "A Bottom-Up Approach to the Primate Mind," Frans B.M. de Waal and Pier Francesco Ferrari note that neurophysiological studies show that specific neuron assemblies in the rat hippocampus are active during memory retrieval and that those same assemblies predict future choices. This would suggest that episodic memory and future orientation aren't as advanced a process as Donald posits in his Theory of Mind. Also, neuroimaging studies in humans show that the cortical areas active during observations of another's actions are related in position and structure to those areas identified as containing mirror neurons in macaques. Could this point to a physiological basis for imitation? ... (Scott Curtis)"

0.0037292899 = product of:
  0.022375738 = sum of:
    0.022375738 = product of:
      0.044751476 = sum of:
        0.044751476 = weight(_text_:theory in 2125) [ClassicSimilarity], result of:
          0.044751476 = score(doc=2125,freq=2.0), product of:
            0.16234003 = queryWeight, product of:
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.03903913 = queryNorm
            0.27566507 = fieldWeight in 2125, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.1583924 = idf(docFreq=1878, maxDocs=44218)
              0.046875 = fieldNorm(doc=2125)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Abstract

The article analyzes user-IR system interaction from the broad, socio-cognitive perspective of lessons we can learn about human brain evolution when we compare the Neanderthal brain to the human brain before and after a small human brain mutation is hypothesized to have occurred 35,000-75,000 years ago. The enhanced working memory mutation enabled modern humans (i) to decode unfamiliar environmental stimuli with greater focusing power on adaptive solutions to environmental changes and problems, and (ii) to encode environmental stimuli in more efficient, generative knowledge structures. A sociological theory of these evolving, more efficient encoding knowledge structures is given. These new knowledge structures instilled in humans not only the ability to adapt to and survive novelty and/or changing conditions in the environment, but they also instilled an imperative to do so. Present day IR systems ignore the encoding imperative in their design framework. To correct for this lacuna, we propose the evolutionary-based socio-cognitive framework model for designing interactive IR systems. A case study is given to illustrate the functioning of the model.

0.0026446318 = product of:
  0.01586779 = sum of:
    0.01586779 = product of:
      0.03173558 = sum of:
        0.03173558 = weight(_text_:22 in 3675) [ClassicSimilarity], result of:
          0.03173558 = score(doc=3675,freq=2.0), product of:
            0.1367084 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03903913 = queryNorm
            0.23214069 = fieldWeight in 3675, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=3675)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Date

22. 5.1999 14:51:49

0.0023239423 = product of:
  0.013943653 = sum of:
    0.013943653 = product of:
      0.027887305 = sum of:
        0.027887305 = weight(_text_:methods in 36) [ClassicSimilarity], result of:
          0.027887305 = score(doc=36,freq=2.0), product of:
            0.15695344 = queryWeight, product of:
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.03903913 = queryNorm
            0.17767884 = fieldWeight in 36, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0204134 = idf(docFreq=2156, maxDocs=44218)
              0.03125 = fieldNorm(doc=36)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Abstract

There have been various approaches to conceptualizing interactive information retrieval (IR), which can be generally divided into system and user approaches (Hearst, 1999; cf. also Spink, 1997). Both system and user approaches define user-system interaction in terms of the system and the user reacting to the actions or behaviors of the other: the system reacts to the user's input; the user to the output of the system (Spink, 1997). In system approach models of the interaction, e.g., Moran (1981), "[T]he user initiates an action or operation and the system responds in some way which in turn leads the user to initiate another action and so on" (Beaulieu, 2000, p. 433). In its purest form, the system approach models the user as a reactive part of the interaction, with the system taking the lead (Bates, 1990). User approaches, on the other hand, in their purest form wish to insert a model of the user in all its socio-cognitive dimensions, to the extent that system designers consider such approaches impractical (Vakkari and Jarvelin, 2005, Chap. 7, this volume). The cognitive approach to IR interaction attempts to overcome this divide (Ruthven, 2005, Chap. 4, this volume; Vakkari and Jarvelin, 2005 Chap. 7, this volume) by representing the cognitive elements of both system designers and the user in the interaction model (Larsen and Ingwersen, 2005 Chap. 3, this volume). There are cognitive approach researchers meeting in a central ground from both the system and user side. On the system side, are computer scientists employing cognitive research to design more effective IR systems from the point of view of the user's task (Nathan, 1990; Fischer, Henninger, and Redmiles, 1991; O'Day and Jeffries, 1993; Russell et al., 1993; Kitajima and Polson, 1996; Terwilliger and Polson, 1997). On the user side are cognitive approach researchers applying methods, concepts and models from psychology to design systems that are more in tune with how users acquire information (e.g., Belkin, 1980; Ford (2005, Chap. 5, this volume); Ingwersen (Larsen and Ingwersen, 2005, Chap. 3, this volume); Saracevic, 1996; Vakkari (Vakkari and Jarvelin, 2005, Chap. 7, this volume)).

0.0022238651 = product of:
  0.01334319 = sum of:
    0.01334319 = product of:
      0.02668638 = sum of:
        0.02668638 = weight(_text_:29 in 4588) [ClassicSimilarity], result of:
          0.02668638 = score(doc=4588,freq=2.0), product of:
            0.13732746 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03903913 = queryNorm
            0.19432661 = fieldWeight in 4588, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4588)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Date

4. 4.2000 13:29:38

0.0022238651 = product of:
  0.01334319 = sum of:
    0.01334319 = product of:
      0.02668638 = sum of:
        0.02668638 = weight(_text_:29 in 1819) [ClassicSimilarity], result of:
          0.02668638 = score(doc=1819,freq=2.0), product of:
            0.13732746 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03903913 = queryNorm
            0.19432661 = fieldWeight in 1819, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1819)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Date

26. 4.2015 19:49:29

0.0022038599 = product of:
  0.013223159 = sum of:
    0.013223159 = product of:
      0.026446318 = sum of:
        0.026446318 = weight(_text_:22 in 667) [ClassicSimilarity], result of:
          0.026446318 = score(doc=667,freq=2.0), product of:
            0.1367084 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03903913 = queryNorm
            0.19345059 = fieldWeight in 667, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=667)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Date

22. 3.2013 19:41:17

0.0017630879 = product of:
  0.010578527 = sum of:
    0.010578527 = product of:
      0.021157054 = sum of:
        0.021157054 = weight(_text_:22 in 642) [ClassicSimilarity], result of:
          0.021157054 = score(doc=642,freq=2.0), product of:
            0.1367084 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03903913 = queryNorm
            0.15476047 = fieldWeight in 642, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=642)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)

Date

19. 1.2007 12:55:22