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  • × author_ss:"Belkin, N.J."
  1. Belkin, N.J.: ¬The problem of 'matching' in information retrieval (1980) 0.00 
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  2. Belkin, N.J.; Croft, W.B.: Information filtering and information retrieval : two sides of the same coin? (1992) 0.00 
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  3. Belkin, N.J.; Cool, C.; Koenemann, J.; Ng, K.B.; Park, S.: Using relevance feedback and ranking in interactive searching (1996) 0.00 
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  4. Dumais, S.T.; Belkin, N.J.: ¬The TREC interactive tracks : putting the user into search (2005) 0.00 
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  5. Yuan, X.; Belkin, N.J.: Investigating information retrieval support techniques for different information-seeking strategies (2010) 0.00 
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    Abstract
    We report on a study that investigated the efficacy of four different interactive information retrieval (IIR) systems, each designed to support a specific information-seeking strategy (ISS). These systems were constructed using different combinations of IR techniques (i.e., combinations of different methods of representation, comparison, presentation and navigation), each of which was hypothesized to be well suited to support a specific ISS. We compared the performance of searchers in each such system, designated experimental, to an appropriate baseline system, which implemented the standard specified query and results list model of current state-of-the-art experimental and operational IR systems. Four within-subjects experiments were conducted for the purpose of this comparison. Results showed that each of the experimental systems was superior to its baseline system in supporting user performance for the specific ISS (that is, the information problem leading to that ISS) for which the system was designed. These results indicate that an IIR system, which intends to support more than one kind of ISS, should be designed within a framework which allows the use and combination of different IR support techniques for different ISSs.
    Type
    a
  6. 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.
    Type
    a
  7. 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.
    Type
    a
  8. Belkin, N.J.: ¬The use of multiple information problem representation for information retrieval (1994) 0.00 
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    Abstract
    Discusses the general issues of the effect and use of multiple representations of the same information problem, or topics, on information retrieval system performance. It has been known for some time that different representations of the same information problem retrieve different sets (or lists) of documents, both relevant and non-relevant. More recently, there have been a number of studies investigating the effects of combining, in various ways, such different representations, in order to try to get a single response from the information retrieval system which is better than that for any of the single representations. Discusses the rationale, both empirical and theoretical, for such an approach, and surveys the results of recent research projects in this area. All of them demonstrate the same phenomenon; the more representations one can combine, the better the retrieval performance. Discusses the implications of these results for information retrieval system design and information retrieval
    Type
    a
  9. 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.
    Type
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  10. 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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  11. Daniels, P.J.; Brooks, H.M.; Belkin, N.J.: Using problem structures for driving human-computer dialogues (1985) 0.00 
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  12. Savage-Knepshield, P.A.; Belkin, N.J.: Interaction in information retrieval : trends over time (1999) 0.00 
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  13. 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
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