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Information mapping

About: Information mapping is a research topic. Over the lifetime, 1137 publications have been published within this topic receiving 32016 citations. The topic is also known as: Information mapping method.


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Journal ArticleDOI
TL;DR: Models are proposed that show how organizations can be designed to meet the information needs of technology, interdepartmental relations, and the environment to both reduce uncertainty and resolve equivocality.
Abstract: This paper answers the question, "Why do organizations process information?" Uncertainty and equivocality are defined as two forces that influence information processing in organizations. Organization structure and internal systems determine both the amount and richness of information provided to managers. Models are proposed that show how organizations can be designed to meet the information needs of technology, interdepartmental relations, and the environment. One implication for managers is that a major problem is lack of clarity, not lack of data. The models indicate how organizations can be designed to provide information mechanisms to both reduce uncertainty and resolve equivocality.

8,674 citations

Journal ArticleDOI
TL;DR: Arrow and Taylor as mentioned in this paper suggest that organizations systematically gather more information than they use, and yet continue to ask for more, and suggest that this behavior is a consequence of some ways in which organizational settings for information use differ from those anticipated in a simple decision-theory vision.
Abstract: We are grateful for the comments of Kenneth Arrow, Kennette Benedict, Robert Biller, David Brereton, Louise Comfort, Jerry Feldman, Victor Fuchs, Anne Miner, J. Rounds, Alan Saltzstein, Guje Sevon, and J. Serge Taylor; for the assistance of Julia Ball; and for grants from the Spencer Foundation, Brookings Institution, Hoover Institution, and National Institute of Education. Formal theories of rational choice suggest that information about the possible consequences of alternative actions will be sought and used only if the precision, relevance, and reliability of the information are compatible with its cost. Empirical studies of information in organizations portray a pattern that is hard to rationalize in such terms. In particular, organizations systematically gather more information than they use, yet continue to ask for more. We suggest that this behavior is a consequence of some ways in which organizational settings for information use differ from those anticipated in a simple decision-theory vision. In particular, the use of information is embedded in social normsthat make it highly symbolic. Some of the implications of such a pattern of information use are discussed.

1,594 citations

Journal ArticleDOI
TL;DR: The aim of this paper is to attempt to reduce confusion by devoting attention to the definition of some concepts and by proposing the basis for a theory of the motivations for information‐seeking behaviour.
Abstract: Apart from information retrieval there is virtually no other area of information science that has occasioned as much research effort and writing as ‘user studies’. Within user studies the investigation of ‘information needs’ has been the subject of much debate and no little confusion. The aim of this paper is to attempt to reduce this confusion by devoting attention to the definition of some concepts and by proposing the basis for a theory of the motivations for information‐seeking behaviour.

1,563 citations

Journal ArticleDOI
TL;DR: The attempt in this paper to automate the whole process not only helps create final patent maps for topic analyses, but also facilitates or improves other patent analysis tasks such as patent classification, organization, knowledge sharing, and prior art searches.
Abstract: Patent documents contain important research results. However, they are lengthy and rich in technical terminology such that it takes a lot of human efforts for analyses. Automatic tools for assisting patent engineers or decision makers in patent analysis are in great demand. This paper describes a series of text mining techniques that conforms to the analytical process used by patent analysts. These techniques include text segmentation, summary extraction, feature selection, term association, cluster generation, topic identification, and information mapping. The issues of efficiency and effectiveness are considered in the design of these techniques. Some important features of the proposed methodology include a rigorous approach to verify the usefulness of segment extracts as the document surrogates, a corpus- and dictionary-free algorithm for keyphrase extraction, an efficient co-word analysis method that can be applied to large volume of patents, and an automatic procedure to create generic cluster titles for ease of result interpretation. Evaluation of these techniques was conducted. The results confirm that the machine-generated summaries do preserve more important content words than some other sections for classification. To demonstrate the feasibility, the proposed methodology was applied to a real-world patent set for domain analysis and mapping, which shows that our approach is more effective than existing classification systems. The attempt in this paper to automate the whole process not only helps create final patent maps for topic analyses, but also facilitates or improves other patent analysis tasks such as patent classification, organization, knowledge sharing, and prior art searches.

695 citations

Journal ArticleDOI
TL;DR: In this paper, a set of ideas, concepts, models, and procedures appropriate to information manufacturing systems that can be used to determine the quality of information products delivered, or transferred, to information customers are presented.
Abstract: Many of the concepts and procedures of product quality control can be applied to the problem of producing better quality information outputs. From this perspective, information outputs can be viewed as information products, and many information systems can be modeled as information manufacturing systems. The use of information products is becoming increasingly prevalent both within and across organizational boundaries. This paper presents a set of ideas, concepts, models, and procedures appropriate to information manufacturing systems that can be used to determine the quality of information products delivered, or transferred, to information customers. These systems produce information products on a regular or as-requested basis. The model systematically tracks relevant attributes of the information product such as timeliness, accuracy and cost. This is facilitated through an information manufacturing analysis matrix that relates data units and various system components. Measures of these attributes can then be used to analyze potential improvements to the information manufacturing system under consideration. An illustrative example is given to demonstrate the various features of the information manufacturing system and show how it can be used to analyze and improve the system. Following that is an actual application, which, although not as involved as the illustrative example, does demonstrate the applicability of the model and its associated concepts and procedures.

560 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20232
20222
20213
202010
201913
201813