Search (9 results, page 1 of 1)

0.0068155187 = product of:
  0.027262075 = sum of:
    0.027262075 = weight(_text_:information in 4474) [ClassicSimilarity], result of:
      0.027262075 = score(doc=4474,freq=42.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.44440612 = fieldWeight in 4474, product of:
          6.4807405 = tf(freq=42.0), with freq of:
            42.0 = termFreq=42.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4474)
  0.25 = coord(1/4)

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.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.7, S.1216-1231

Theme

Information

0.0065844175 = product of:
  0.02633767 = sum of:
    0.02633767 = weight(_text_:information in 837) [ClassicSimilarity], result of:
      0.02633767 = score(doc=837,freq=20.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.42933714 = fieldWeight in 837, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0546875 = fieldNorm(doc=837)
  0.25 = coord(1/4)

Abstract

This paper outlines the relation between philosophy of information (PI) and human information behavior (HIB). In this paper, we first briefly outline the basic constructs and approaches of PI and HIB. We argue that a strong relation exists between PI and HIB, as both are exploring the concept of information and premise information as a fundamental concept basic to human existence. We then exemplify that a heuristic approach to PI integrates the HIB view of information as a cognitive human-initiated process by presenting a specific cognitive architecture for information initiation based on modular notion from HIB/evolutionary psychology and the vacuum mechanism from PI.

Footnote

Artikel in einem Themenheft: The philosophy of information

Theme

Information

0.0063099447 = product of:
  0.025239779 = sum of:
    0.025239779 = weight(_text_:information in 4915) [ClassicSimilarity], result of:
      0.025239779 = score(doc=4915,freq=36.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.41144013 = fieldWeight in 4915, product of:
          6.0 = tf(freq=36.0), with freq of:
            36.0 = termFreq=36.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4915)
  0.25 = coord(1/4)

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.

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.1, S.25-35

Theme

Information

0.0062465263 = product of:
  0.024986105 = sum of:
    0.024986105 = weight(_text_:information in 7747) [ClassicSimilarity], result of:
      0.024986105 = score(doc=7747,freq=18.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.40730494 = fieldWeight in 7747, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0546875 = fieldNorm(doc=7747)
  0.25 = coord(1/4)

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

Source

Journal of the American Society for Information Science. 45(1994) no.7, S.465-476

Theme

Information

0.0059192525 = product of:
  0.02367701 = sum of:
    0.02367701 = weight(_text_:information in 3675) [ClassicSimilarity], result of:
      0.02367701 = score(doc=3675,freq=22.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.38596505 = fieldWeight in 3675, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=3675)
  0.25 = coord(1/4)

Abstract

This article is about the mental coding processes involved in the flow of 'information' when the user is interacting with an 'enabling' information retrieval system. An 'enabling' IR system is designed to stimulate the user's grasping towards a higher understanding of the information need / problem / task that brought the user to the IR system. C. Shannon's (1949/1959) model of the flow of information and K.R. Popper's (1975) 3 worlds concept are used to diagram the flow of information between the user and system when the user receives a stimulating massage, with particluar emphasis on the decoding and encoding operations involved as the user processes the message. The key difference between the model of information flow proposed here and the linear transmission, receiver-oriented model now in use is that we assume that users of a truly interactive, 'enabling' IR system are primarily message senders, not passive receivers of the message, because they must create a new message back to the system, absed on a reconceptualization of their information need, while they are 'online' interacting with the system

Source

Journal of the American Society for Information Science. 50(1999) no.6, S.544-552

Theme

Information

0.0058892816 = product of:
  0.023557127 = sum of:
    0.023557127 = weight(_text_:information in 4069) [ClassicSimilarity], result of:
      0.023557127 = score(doc=4069,freq=16.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.3840108 = fieldWeight in 4069, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0546875 = fieldNorm(doc=4069)
  0.25 = coord(1/4)

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

Source

Journal of the American Society for Information Science. 44(1993) no.4, S.204-211

Theme

Information

0.0047031553 = product of:
  0.018812621 = sum of:
    0.018812621 = weight(_text_:information in 4585) [ClassicSimilarity], result of:
      0.018812621 = score(doc=4585,freq=20.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.30666938 = fieldWeight in 4585, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4585)
  0.25 = coord(1/4)

Abstract

With new interactive technology, we can increase user satisfaction by designing information retrieval systems that inform the user while the user is on-line interacting with the system. The purpose of this article is to model the information processing operations of a generic user who has just received an information message from the system and is stimulated by the message into grasping at a higher understanding of his or her information task or problem. The model consists of 3 levels, each of which forms a separate subsystem. In the Perseption subsystem, the user perceives the system message in a visual sense; in the Comprehension subsystem, the user must comprehend the system message; and in the Application subsystem, the user must (a) interpret the system message in terms of the user's task at hand, and (b) create and send a new message back to the system to complete the interaction. Because of the information process stimulated by the interaction, the user's new message forms a query to the system that more accurately represents the user's information need than would have been the case if the interaction had not taken place. This article proposes a device to enable clarification of the user's task, and thus his/her information need at the Application subsystem level of the model

Source

Journal of the American Society for Information Science. 51(2000) no.5, S.417-426

Theme

Information

0.0042066295 = product of:
  0.016826518 = sum of:
    0.016826518 = weight(_text_:information in 5161) [ClassicSimilarity], result of:
      0.016826518 = score(doc=5161,freq=16.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.27429342 = fieldWeight in 5161, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5161)
  0.25 = coord(1/4)

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

Source

Journal of the American Society for Information Science. 51(2000) no.11, S.1033-1046

Theme

Information

0.003889711 = product of:
  0.015558844 = sum of:
    0.015558844 = weight(_text_:information in 480) [ClassicSimilarity], result of:
      0.015558844 = score(doc=480,freq=38.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.25362873 = fieldWeight in 480, product of:
          6.164414 = tf(freq=38.0), with freq of:
            38.0 = termFreq=38.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0234375 = fieldNorm(doc=480)
  0.25 = coord(1/4)

Abstract

What is the uniquely human factor in finding and using information to produce new knowledge? Is there an underlying aspect of our thinking that cannot be imitated by the AI-equipped machines that will increasingly dominate our lives? This book answers these questions, and tells us about our consciousness - its drive or intention in seeking information in the world around us, and how we are able to construct new knowledge from this information. The book is divided into three parts, each with an introduction and a conclusion that relate the theories and models presented to the real-world experience of someone using a search engine. First, Part I defines the exceptionality of human consciousness and its need for new information and how, uniquely among all other species, we frame our interactions with the world. Part II then investigates the problem of finding our real information need during information searches, and how our exceptional ability to frame our interactions with the world blocks us from finding the information we really need. Lastly, Part III details the solution to this framing problem and its operational implications for search engine design for everyone whose objective is the production of new knowledge. In this book, Charles Cole deliberately writes in a conversational style for a broader readership, keeping references to research material to the bare minimum. Replicating the structure of a detective novel, he builds his arguments towards a climax at the end of the book. For our video-game, video-on-demand times, he has visualized the ideas that form the book's thesis in over 90 original diagrams. And above all, he establishes a link between information need and knowledge production in evolutionary psychology, and thus bases his arguments in our origins as a species: how we humans naturally think, and how we naturally search for new information because our consciousness drives us to need it.

Footnote

Rez. in: JASIST 71(2020) no.1, S.118-120 (Heidi Julien). - Vgl. auch den Beitrag: Cole, C.: A rebuttal of the book review of the book titled "The Consciousness' Drive: Information Need and the Search for Meaning": mapping cognitive and document spaces. In: Journal of the Association for Information Science and Technology. 71(2020) no.2, S.242.
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.

LCSH

Information Storage and Retrieval

Subject

Information Storage and Retrieval

Theme

Information