Search (31 results, page 2 of 2)

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Source

Journal of the American Society for Information Science. 34(1983), S.163-180

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Abstract

Reports on part of a study of real users' behaviour in selecting documents from a list of citations resulting from a search of an information retrieval system. Document selection involves value judgements and decision making. Understanding how users evaluate documents and make decisions provides a basis for designing intelligent information retrieval system that can do a better job of predicting usefulness

Imprint

Medford, NJ : Learned Information

Source

Integrating technologies - converging professions: proceedings of the 56th Annual Meeting of the American Society for Information Science, Columbus, OH, 24-28 October 1993. Ed.: S. Bonzi

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Abstract

Throughout an information search, a user needs to make sense of the information found to create an understanding. This requires cognitive effort that can be demanding. Building on prior sensemaking models and expanding them with ideas from learning and cognitive psychology, we examined the use of cognitive mechanisms during individual sensemaking. We conducted a qualitative user study of 15 students who searched for and made sense of information for business analysis and news writing tasks. Through the analysis of think-aloud protocols, recordings of screen movements, intermediate work products of sensemaking, including notes and concept maps, and final reports, we observed the use of 17 data-driven and structure-driven mechanisms for processing new information, examining individual concepts and relationships, and detecting anomalies. These cognitive mechanisms, as the basic operators that move sensemaking forward, provide in-depth understanding of how people process information to produce sense. Meaningful learning and sensemaking are closely related, so our findings apply to learning as well. Our results contribute to a better understanding of the sensemaking process-how people think-and this better understanding can inform the teaching of thinking skills and the design of improved sensemaking assistants and mind tools.

Source

Journal of the Association for Information Science and Technology. 71(2020) no.2, S.158-171

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Source

Journal of digital information. 4(2004) no.4, art.#257

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Abstract

Synthesizing and building on many ideas from the literature, this article presents an improved conceptual framework that clarifies the notion of relevance with its many elements, variables, criteria, and situational factors. Relevance is defined as a Relationship (R) between an Information Object (I) and an Information Need (N) (which consists of Topic, User, Problem/Task, and Situation/Context) with focus on R. This defines Relevance-as-is (conceptual relevance, strong relevance). To determine relevance, an Agent A (a person or system) operates on a representation I? of the information object and a representation N? of the information need, resulting in relevance-as-determined (operational measure of relevance, weak relevance, an approximation). Retrieval tests compare relevance-as-determined by different agents. This article discusses and compares two major approaches to conceptualizing relevance: the entity-focused approach (focus on elaborating the entities involved in relevance) and the relationship-focused approach (focus on explicating the relational nature of relevance). The article argues that because relevance is fundamentally a relational construct the relationship-focused approach deserves a higher priority and more attention than it has received. The article further elaborates on the elements of the framework with a focus on clarifying several critical issues on the discourse on relevance.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.1, S.18-35

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Abstract

This article proposes a model of document selection by real users of a bibliographic retrieval system. It reports on Part 1 of a longitudinal study of decision making on document use by academics during a actual research project. (Part 2 followed up the same users on how the selected documents were actually used in subsequent stages). The participants are 25 self-selected faculty and graduate students in Agricultural Economics. After a reference interview, the researcher conducted a search of DIALOG databases and prepared a printout. The users selected documents from this printout, They were asked to read and think aloud while selecting documents. There verbal reports were recorded and analyzed from a utiliy-theoretic perspective. The following model of the decision-making in the selection process emerged: document information lemenets (DIEs) in document records provide the information for judging the documents on 11 criteria (including topicality, orientation, quality, novelty, and authority); the criteria judgments are comninded in an assessment of document value along 5 dimensions (Epistemic, functional, conditional, social, and emotional values), leading to the use decision. This model accounts for the use of personal knowledge and decision strategies applied in the selection process. The model has implications for the design of an intelligent document selection assistant

Source

Journal of the American Society for Information Science. 49(1998) no.2, S.115-133

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Abstract

Tools for automatic subject assignment help deal with scale and sustainability in creating and enriching metadata, establishing more connections across and between resources and enhancing consistency. Although some software vendors and experimental researchers claim the tools can replace manual subject indexing, hard scientific evidence of their performance in operating information environments is scarce. A major reason for this is that research is usually conducted in laboratory conditions, excluding the complexities of real-life systems and situations. The article reviews and discusses issues with existing evaluation approaches such as problems of aboutness and relevance assessments, implying the need to use more than a single "gold standard" method when evaluating indexing and retrieval, and proposes a comprehensive evaluation framework. The framework is informed by a systematic review of the literature on evaluation approaches: evaluating indexing quality directly through assessment by an evaluator or through comparison with a gold standard, evaluating the quality of computer-assisted indexing directly in the context of an indexing workflow, and evaluating indexing quality indirectly through analyzing retrieval performance.

Series

Advances in information science

Source

Journal of the Association for Information Science and Technology. 67(2016) no.1, S.3-16

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Source

International forum on information and documentation. 4(1979) no.3, S.21-24

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Abstract

As an attempt to make a general structural theory of information retrieval, a documentation system (DS) is defined as a formal system consisting of (a) a set o of objects (documents); (b) a set A++ of elementary attributes (key-words), from which further attributes may be constructed: A++ generates A; (c) a set of axioms of the form X++(x)=m (m¯M, M a set of constant connecting attributes with objects: from the axioms further theorems (=true statements) may be constructed. By use of the theorems, different mappings O -> P(o) (P(o) set of all subsets of o) (search question -> set of documents retrieved) are defined. The type of a DS depends on two basic decisions: (1) choice of the rules for the construction of attributes and theorems, e.g., logical product in coordinate indexing; links. (2) choice of M; M may consist of the two constants 'applicable' and 'not applicable', or some positive integers, ...; Further practical decisions: A++ hierarchical or not; kind of mapping; introduction of roles (=further attributes). The most simple case - ordinary two-valued Coordinate Indexing - is discusssed in detail; o is a free distributive (but not Boolean) lattice, the homographic image a ring of subsets of o; instead of negation which is not useful, a useful retrieval operation 'praeternagation' is introduced. Furthermore these are discussed: a generalized definition of superimposed coding, some functions for the distance of objects or attributes; optimization and automatic derivation of classifications. The model takes into account term-term relations and document-document relations. It may serve as a structural framework in terms of which the functional problems of retrieval theory may be expressed more clearly

Source

Information storage and retrieval. 3(1967), S.129-173

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Source

Journal of the American Society for Information Science. 45(1994) no.8, S.589-599

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Source

Journal of the Association for Information Science and Technology. 66(2015) no.8, S.1616-1644