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  • × author_ss:"Belkin, N.J."
  1. Belkin, N.J.: ¬An overview of results from Rutgers' investigations of interactive information retrieval (1998) 0.01 
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    Abstract
    Over the last 4 years, the Information Interaction Laboratory at Rutgers' School of communication, Information and Library Studies has performed a series of investigations concerned with various aspects of people's interactions with advanced information retrieval (IR) systems. We have benn especially concerned with understanding not just what people do, and why, and with what effect, but also with what they would like to do, and how they attempt to accomplish it, and with what difficulties. These investigations have led to some quite interesting conclusions about the nature and structure of people's interactions with information, about support for cooperative human-computer interaction in query reformulation, and about the value of visualization of search results for supporting various forms of interaction with information. In this discussion, I give an overview of the research program and its projects, present representative results from the projects, and discuss some implications of these results for support of subject searching in information retrieval systems
    Date
    22. 9.1997 19:16:05
    Imprint
    Urbana-Champaign, IL : Illinois University at Urbana-Champaign, Graduate School of Library and Information Science
    Source
    Visualizing subject access for 21st century information resources: Papers presented at the 1997 Clinic on Library Applications of Data Processing, 2-4 Mar 1997, Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign. Ed.: P.A. Cochrane et al
  2. Daniels, P.J.; Brooks, H.M.; Belkin, N.J.: Using problem structures for driving human-computer dialogues (1985) 0.00 
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.135-142.
  3. Belkin, N.J.; Croft, W.B.: Retrieval techniques (1987) 0.00 
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    Source
    Annual review of information science and technology. 22(1987), S.109-145
  4. Belkin, N.J.: Intelligent information retrieval : whose intelligence? (1996) 0.00 
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    Abstract
    The concept of 'intelligent' information retrieval was first mooted in the late 1970s, but had lost currency within the information retrieval community by at least the early 1990s. With the popularity of the concept of 'intelligent agents', it appears that the idea of intelligent information retrieval is again in general vogue. In this paper, I attempt to show that the naive concept of intelligent information retrieval, based on the the idea of agency, misses the essence of intelligence in the information retrieval system, and will inevitably lead to dysfunctional information retrieval. As a counter-proposal, I suggest that true intelligence in information retrieval resides in appropriate allocation of responsibility amongst all the actors in the information retrieval system, and that intelligent information retrieval will be achieved through effective support of people in their various interactions with information
    Source
    Herausforderungen an die Informationswirtschaft: Informationsverdichtung, Informationsbewertung und Datenvisualisierung. Proceedings des 5. Internationalen Symposiums für Informationswissenschaft (ISI'96), Humboldt-Universität zu Berlin, 17.-19. Oktober 1996. Hrsg.: J. Krause u.a
  5. Belkin, N.J.; Marchetti, P.G.; Cool, C.: BRAQUE: design of an interface to support user interaction in information retrieval (1993) 0.00 
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    Source
    Information processing and management. 29(1993) no.3, S.325-344
  6. Belkin, N.J.: ¬The cognitive viewpoint in information science (1990) 0.00 
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    Source
    Journal of information science. 16(1990), S.11-15
  7. Belkin, N.J.; Croft, W.B.: Information filtering and information retrieval : two sides of the same coin? (1992) 0.00 
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    Abstract
    One of nine articles in this issue of Communications of the ACM devoted to information filtering
    Source
    Communications of the Association for Computing Machinery. 35(1992) no.12, S.29-38
  8. Dumais, S.T.; Belkin, N.J.: ¬The TREC interactive tracks : putting the user into search (2005) 0.00 
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    Date
    29. 3.1996 18:16:49
    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  9. Savage-Knepshield, P.A.; Belkin, N.J.: Interaction in information retrieval : trends over time (1999) 0.00 
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    Content
    Beitrag eines Themenheftes: The 50th Anniversary of the Journal of the American Society for Information Science. Pt.2: Paradigms, models, and models of information science
    Source
    Journal of the American Society for Information Science. 50(1999) no.12, S.1067-1082
  10. Belkin, N.J.; Vickery, A.: Interaction in information systems : a review of research from document retrieval to knowledge-based systems (1985) 0.00 
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    Series
    Library and information science report; 35
  11. Belkin, N.J.: ¬The problem of 'matching' in information retrieval (1980) 0.00 
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    Source
    Theory and application of information research. Proc. of the 2nd Int. Research Forum on Information Science, 3.-6.8.1977, Copenhagen. Ed.: O. Harbo u. L. Kajberg
  12. Yuan, X. (J.); Belkin, N.J.: Applying an information-seeking dialogue model in an interactive information retrieval system (2014) 0.00 
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    Abstract
    Purpose - People often engage in different information-seeking strategies (ISSs) within a single information-seeking episode. A critical concern for the design of information retrieval (IR) systems is how to provide support for these different behaviors in a manner which searchers can easily understand, navigate and use, as they move from one ISS to another. The purpose of this paper is to describe a dialogue structure that was implemented in an experimental IR system, in order to address this concern. Design/methodology/approach - The authors conducted a user-centered experiment to evaluate the IR systems. Participants were asked to search for information on two different task types, with four different topics per task, in both the experimental system and a baseline system emulating state-of-the-art IR systems. The authors report here the results related explicitly to the use of the experimental system's dialogue structure. Findings - For one of the task types, most participants followed the search steps as predicted in the dialogue structures, and those who did so completed the task in fewer moves. For the other task type, predicted order of moves was often not followed, but participants again used fewer moves when following the predicted order. Results demonstrate that the dialogue structures the authors designed indeed support effective human information behavior patterns in a variety of ways, and that searchers can effectively use a system which changes to support different ISSs. Originality/value - This study shows that it is both possible and beneficial, to design an IR system which can support multiple ISSs, and that such a system can be understood and used successfully.
    Date
    6. 4.2015 19:22:59
  13. Li, Y.; Belkin, N.J.: ¬A faceted approach to conceptualizing tasks in information seeking (2008) 0.00 
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    Abstract
    The nature of the task that leads a person to engage in information interaction, as well as of information seeking and searching tasks, have been shown to influence individuals' information behavior. Classifying tasks in a domain has been viewed as a departure point of studies on the relationship between tasks and human information behavior. However, previous task classification schemes either classify tasks with respect to the requirements of specific studies or merely classify a certain category of task. Such approaches do not lead to a holistic picture of task since a task involves different aspects. Therefore, the present study aims to develop a faceted classification of task, which can incorporate work tasks and information search tasks into the same classification scheme and characterize tasks in such a way as to help people make predictions of information behavior. For this purpose, previous task classification schemes and their underlying facets are reviewed and discussed. Analysis identifies essential facets and categorizes them into Generic facets of task and Common attributes of task. Generic facets of task include Source of task, Task doer, Time, Action, Product, and Goal. Common attributes of task includes Task characteristics and User's perception of task. Corresponding sub-facets and values are identified as well. In this fashion, a faceted classification of task is established which could be used to describe users' work tasks and information search tasks. This faceted classification provides a framework to further explore the relationships among work tasks, search tasks, and interactive information retrieval and advance adaptive IR systems design.
    Date
    22.11.2008 16:29:21
    Footnote
    Beitrag in einem Themenheft "Adaptive information retrieval"
  14. Belkin, N.J.; Chang, S.J.; Downs, T.; Saracevic, T.; Zhao, S.: Taking account of user tasks, goals and behavior for the design of online public access catalogs (1990) 0.00 
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    Source
    ASIS'90: Information in the year 2000: from research to application. Proc. 33rd Annual Meeting of the American Society for Information Science
  15. Belkin, N.J.; Marchetti, P.G.; Albrecht, M.; Fusco, L.; Skogvold, S.; Stokke, H.; Troina, G.: User interfaces for information systems (1991) 0.00 
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    Abstract
    This paper presents descriptions of four information / system interface projects in progress at ESRIN, the astablishment of the European Space Agency (ESA) in Italy. Each project demonstrates a somewhat different approach to interface design, but all share the commonality of responding to user goals, tasks and characteristics. It is suggested that next generation scientific information systems will have to be designed for direct access by end users to a large variety of information sources, through a common interface. Design of such systems, including their interfaces, should be based on a multi-level analysis of user goals, tasks and domain views.
    Source
    Journal of information science. 17(1991), S.327-344
  16. Yuan, X.; Belkin, N.J.: Evaluating an integrated system supporting multiple information-seeking strategies (2010) 0.00 
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    Abstract
    Many studies have demonstrated that people engage in a variety of different information behaviors when engaging in information seeking. However, standard information retrieval systems such as Web search engines continue to be designed to support mainly one such behavior, specified searching. This situation has led to suggestions that people would be better served by information retrieval systems which support different kinds of information-seeking strategies. This article reports on an experiment comparing the retrieval effectiveness of an integrated interactive information retrieval (IIR) system which adapts to support different information-seeking strategies with that of a standard baseline IIR system. The experiment, with 32 participants each searching on eight different topics, indicates that using the integrated IIR system resulted in significantly better user satisfaction with search results, significantly more effective interaction, and significantly better usability than that using the baseline system.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.10, S.1987-2010
  17. Belkin, N.J.; Robertson, S.E: Information science and the phenomenon of information (1976) 0.00 
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    Source
    Journal of the American Society for information science. 27(1976), S.197-204
  18. Liu, J.; Liu, C.; Belkin, N.J.: Predicting information searchers' topic knowledge at different search stages (2016) 0.00 
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    Abstract
    As a significant contextual factor in information search, topic knowledge has been gaining increased research attention. We report on a study of the relationship between information searchers' topic knowledge and their search behaviors, and on an attempt to predict searchers' topic knowledge from their behaviors during the search. Data were collected in a controlled laboratory experiment with 32 undergraduate journalism student participants, each searching on 4 tasks of different types. In general, behavioral variables were not found to have significant differences between users with high and low levels of topic knowledge, except the mean first dwell time on search result pages. Several models were built to predict topic knowledge using behavioral variables calculated at 3 different stages of search episodes: the first-query-round, the middle point of the search, and the end point. It was found that a model using some search behaviors observed in the first query round led to satisfactory prediction results. The results suggest that early-session search behaviors can be used to predict users' topic knowledge levels, allowing personalization of search for users with different levels of topic knowledge, especially in order to assist users with low topic knowledge.
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.11, S.2652-2666
  19. Li, Y.; Belkin, N.J.: ¬An exploration of the relationships between work task and interactive information search behavior (2010) 0.00 
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    Abstract
    This study explores the relationships between work task and interactive information search behavior. Work task was conceptualized based on a faceted classification of task. An experiment was conducted with six work-task types and simulated work-task situations assigned to 24 participants. The results indicate that users present different behavior patterns to approach useful information for different work tasks: They select information systems to search based on the work tasks at hand, different work tasks motivate different types of search tasks, and different facets controlled in the study play different roles in shaping users' interactive information search behavior. The results provide empirical evidence to support the view that work tasks and search tasks play different roles in a user's interaction with information systems and that work task should be considered as a multifaceted variable. The findings provide a possibility to make predictions of a user's information search behavior from his or her work task, and vice versa. Thus, this study sheds light on task-based information seeking and search, and has implications in adaptive information retrieval (IR) and personalization of IR.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.9, S.1771-1789
  20. Liu, J.; Belkin, N.J.: Personalizing information retrieval for multi-session tasks : examining the roles of task stage, task type, and topic knowledge on the interpretation of dwell time as an indicator of document usefulness (2015) 0.00 
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    Abstract
    Personalization of information retrieval tailors search towards individual users to meet their particular information needs by taking into account information about users and their contexts, often through implicit sources of evidence such as user behaviors. This study looks at users' dwelling behavior on documents and several contextual factors: the stage of users' work tasks, task type, and users' knowledge of task topics, to explore whether or not taking account contextual factors could help infer document usefulness from dwell time. A controlled laboratory experiment was conducted with 24 participants, each coming 3 times to work on 3 subtasks in a general work task. The results show that task stage could help interpret certain types of dwell time as reliable indicators of document usefulness in certain task types, as was topic knowledge, and the latter played a more significant role when both were available. This study contributes to a better understanding of how dwell time can be used as implicit evidence of document usefulness, as well as how contextual factors can help interpret dwell time as an indicator of usefulness. These findings have both theoretical and practical implications for using behaviors and contextual factors in the development of personalization systems.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.1, S.58-81

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