-
Baloh, P.; Desouza, K.C.; Hackney, R.: Contextualizing organizational interventions of knowledge management systems : a design science perspectiveA domain analysis (2012)
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- Abstract
- We address how individuals' (workers) knowledge needs influence the design of knowledge management systems (KMS), enabling knowledge creation and utilization. It is evident that KMS technologies and activities are indiscriminately deployed in most organizations with little regard to the actual context of their adoption. Moreover, it is apparent that the extant literature pertaining to knowledge management projects is frequently deficient in identifying the variety of factors indicative for successful KMS. This presents an obvious business practice and research gap that requires a critical analysis of the necessary intervention that will actually improve how workers can leverage and form organization-wide knowledge. This research involved an extensive review of the literature, a grounded theory methodological approach and rigorous data collection and synthesis through an empirical case analysis (Parsons Brinckerhoff and Samsung). The contribution of this study is the formulation of a model for designing KMS based upon the design science paradigm, which aspires to create artifacts that are interdependent of people and organizations. The essential proposition is that KMS design and implementation must be contextualized in relation to knowledge needs and that these will differ for various organizational settings. The findings present valuable insights and further understanding of the way in which KMS design efforts should be focused.
- Date
- 11. 6.2012 14:22:34
- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.5, S.948-966
-
Ravana, S.D.; Rajagopal, P.; Balakrishnan, V.: Ranking retrieval systems using pseudo relevance judgments (2015)
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- Date
- 20. 1.2015 18:30:22
18. 9.2018 18:22:56
- Source
- Aslib journal of information management. 67(2015) no.6, S.700-714
-
Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Date
- 22. 8.2014 17:05:18
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1939-1943
-
Dadashkarimia, J.; Shakery, A.; Failia, H.; Zamani, H.: ¬An expectation-maximization algorithm for query translation based on pseudo-relevant documents (2017)
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- Content
- Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457316306379 [http://dx.doi.org/10.1016/j.ipm.2016.11.007].
- Source
- Information processing and management. 53(2017) no.2, S.371-387
-
Soulier, L.; Jabeur, L.B.; Tamine, L.; Bahsoun, W.: On ranking relevant entities in heterogeneous networks using a language-based model (2013)
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- Date
- 22. 3.2013 19:34:49
- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.500-515
-
Jindal, V.; Bawa, S.; Batra, S.: ¬A review of ranking approaches for semantic search on Web (2014)
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- Source
- Information processing and management. 50(2014) no.2, S.416-425
-
Lee, J.; Min, J.-K.; Oh, A.; Chung, C.-W.: Effective ranking and search techniques for Web resources considering semantic relationships (2014)
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- Source
- Information processing and management. 50(2014) no.1, S.132-155
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Liu, X.; Zheng, W.; Fang, H.: ¬An exploration of ranking models and feedback method for related entity finding (2013)
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- Source
- Information processing and management. 49(2013) no.5, S.995-1007
-
Karisani, P.; Rahgozar, M.; Oroumchian, F.: Transforming LSA space dimensions into a rubric for an automatic assessment and feedback system (2016)
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- Source
- Information processing and management. 52(2016) no.3, S.478-489
-
Hubert, G.; Pitarch, Y.; Pinel-Sauvagnat, K.; Tournier, R.; Laporte, L.: TournaRank : when retrieval becomes document competition (2018)
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- Source
- Information processing and management. 54(2018) no.2, S.252-272
-
Yan, E.; Ding, Y.; Sugimoto, C.R.: P-Rank: an indicator measuring prestige in heterogeneous scholarly networks (2011)
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- Abstract
- Ranking scientific productivity and prestige are often limited to homogeneous networks. These networks are unable to account for the multiple factors that constitute the scholarly communication and reward system. This study proposes a new informetric indicator, P-Rank, for measuring prestige in heterogeneous scholarly networks containing articles, authors, and journals. P-Rank differentiates the weight of each citation based on its citing papers, citing journals, and citing authors. Articles from 16 representative library and information science journals are selected as the dataset. Principle Component Analysis is conducted to examine the relationship between P-Rank and other bibliometric indicators. We also compare the correlation and rank variances between citation counts and P-Rank scores. This work provides a new approach to examining prestige in scholarly communication networks in a more comprehensive and nuanced way.
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.3, S.467-477
-
Van der Veer Martens, B.; Fleet, C. van: Opening the black box of "relevance work" : a domain analysis (2012)
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- Abstract
- In response to Hjørland's recent call for a reconceptualization of the foundations of relevance, we suggest that the sociocognitive aspects of intermediation by information agencies, such as archives and libraries, are a necessary and unexplored part of the infrastructure of the subject knowledge domains central to his recommended "view of relevance informed by a social paradigm" (2010, p. 217). From a comparative analysis of documents from 39 graduate-level introductory courses in archives, reference, and strategic/competitive intelligence taught in 13 American Library Association-accredited library and information science (LIS) programs, we identify four defining sociocognitive dimensions of "relevance work" in information agencies within Hjørland's proposed framework for relevance: tasks, time, systems, and assessors. This study is intended to supply sociocognitive content from within the relevance work domain to support further domain analytic research, and to emphasize the importance of intermediary relevance work for all subject knowledge domains.
- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.5, S.936-947
-
Koumenides, C.L.; Shadbolt, N.R.: Ranking methods for entity-oriented semantic web search (2014)
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- Series
- Advances in information science
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.6, S.1091-1106
-
Li, H.; Wu, H.; Li, D.; Lin, S.; Su, Z.; Luo, X.: PSI: A probabilistic semantic interpretable framework for fine-grained image ranking (2018)
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- Abstract
- Image Ranking is one of the key problems in information science research area. However, most current methods focus on increasing the performance, leaving the semantic gap problem, which refers to the learned ranking models are hard to be understood, remaining intact. Therefore, in this article, we aim at learning an interpretable ranking model to tackle the semantic gap in fine-grained image ranking. We propose to combine attribute-based representation and online passive-aggressive (PA) learning based ranking models to achieve this goal. Besides, considering the highly localized instances in fine-grained image ranking, we introduce a supervised constrained clustering method to gather class-balanced training instances for local PA-based models, and incorporate the learned local models into a unified probabilistic framework. Extensive experiments on the benchmark demonstrate that the proposed framework outperforms state-of-the-art methods in terms of accuracy and speed.
- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.12, S.1488-1501
-
Jacucci, G.; Barral, O.; Daee, P.; Wenzel, M.; Serim, B.; Ruotsalo, T.; Pluchino, P.; Freeman, J.; Gamberini, L.; Kaski, S.; Blankertz, B.: Integrating neurophysiologic relevance feedback in intent modeling for information retrieval (2019)
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- Footnote
- Beitrag in einem 'Special issue on neuro-information science'.
- Source
- Journal of the Association for Information Science and Technology. 70(2019) no.9, S.917-930
-
Fu, X.: Towards a model of implicit feedback for Web search (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.1, S.30-49
-
Efron, M.; Winget, M.: Query polyrepresentation for ranking retrieval systems without relevance judgments (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.6, S.1081-1091
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Cecchini, R.L.; Lorenzetti, C.M.; Maguitman, A.G.; Brignole, N.B.: Multiobjective evolutionary algorithms for context-based search (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.6, S.1258-1274
-
Efron, M.: Linear time series models for term weighting in information retrieval (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.7, S.1299-1312
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Moura, E.S. de; Fernandes, D.; Ribeiro-Neto, B.; Silva, A.S. da; Gonçalves, M.A.: Using structural information to improve search in Web collections (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.12, S.2503-2513
