-
Stvilia, B.; Hinnant, C.C.; Schindler, K.; Worrall, A.; Burnett, G.; Burnett, K.; Kazmer, M.M.; Marty, P.F.: Composition of scientific teams and publication productivity at a national science lab (2011)
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- Date
- 22. 1.2011 13:19:42
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.270-283
-
Ajiferuke, I.; Lu, K.; Wolfram, D.: ¬A comparison of citer and citation-based measure outcomes for multiple disciplines (2010)
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- Date
- 28. 9.2010 12:54:22
- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.10, S.2086-2096
-
Liu, D.-R.; Shih, M.-J.: Hybrid-patent classification based on patent-network analysis (2011)
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- Abstract
- Effective patent management is essential for organizations to maintain their competitive advantage. The classification of patents is a critical part of patent management and industrial analysis. This study proposes a hybrid-patent-classification approach that combines a novel patent-network-based classification method with three conventional classification methods to analyze query patents and predict their classes. The novel patent network contains various types of nodes that represent different features extracted from patent documents. The nodes are connected based on the relationship metrics derived from the patent metadata. The proposed classification method predicts a query patent's class by analyzing all reachable nodes in the patent network and calculating their relevance to the query patent. It then classifies the query patent with a modified k-nearest neighbor classifier. To further improve the approach, we combine it with content-based, citation-based, and metadata-based classification methods to develop a hybrid-classification approach. We evaluate the performance of the hybrid approach on a test dataset of patent documents obtained from the U.S. Patent and Trademark Office, and compare its performance with that of the three conventional methods. The results demonstrate that the proposed patent-network-based approach yields more accurate class predictions than the patent network-based approach.
- Date
- 22. 1.2011 13:04:21
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.246-256
-
Song, M.; Kang, K.; An, J.Y.: Investigating drug-disease interactions in drug-symptom-disease triples via citation relations (2018)
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- Date
- 1.11.2018 18:19:22
- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.11, S.1355-1368
-
Abbasi, M. K.; Frommholz, I.: Cluster-based polyrepresentation as science modelling approach for information retrieval (2015)
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- Source
- Scientometrics. 102(2015) no.3, S.2301-2322
-
Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.4, S.866-867
-
McKeown, K.; Daume III, H.; Chaturvedi, S.; Paparrizos, J.; Thadani, K.; Barrio, P.; Biran, O.; Bothe, S.; Collins, M.; Fleischmann, K.R.; Gravano, L.; Jha, R.; King, B.; McInerney, K.; Moon, T.; Neelakantan, A.; O'Seaghdha, D.; Radev, D.; Templeton, C.; Teufel, S.: Predicting the impact of scientific concepts using full-text features (2016)
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- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.11, S.2684-2696
-
Scholarly metrics under the microscope : from citation analysis to academic auditing (2015)
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- Date
- 22. 1.2017 17:12:50
- Footnote
- Rez. in JASIST 67(2017) no.2, S.537-538 (Ronald Rousseau).
- Pages
- 976 S
- Type
- s
-
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
-
Ohly, P.: Dimensions of globality : a bibliometric analysis (2016)
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- Date
- 20. 1.2019 11:22:31
- Pages
- S.460-468
-
Schreiber, M.: Inconsistencies of recently proposed citation impact indicators and how to avoid them (2012)
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- Abstract
- It is shown that under certain circumstances in particular for small data sets, the recently proposed citation impact indicators I3(6PR) and R(6,k) behave inconsistently when additional papers or citations are taken into consideration. Three simple examples are presented, in which the indicators fluctuate strongly and the ranking of scientists in the evaluated group is sometimes completely mixed up by minor changes in the database. The erratic behavior is traced to the specific way in which weights are attributed to the six percentile rank classes, specifically for the tied papers. For 100 percentile rank classes, the effects will be less serious. For the six classes, it is demonstrated that a different way of assigning weights avoids these problems, although the nonlinearity of the weights for the different percentile rank classes can still lead to (much less frequent) changes in the ranking. This behavior is not undesired because it can be used to correct for differences in citation behavior in different fields. Remaining deviations from the theoretical value R(6,k) = 1.91 can be avoided by a new scoring rule: the fractional scoring. Previously proposed consistency criteria are amended by another property of strict independence at which a performance indicator should aim.
- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.10, S.2062-2073
-
Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015)
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- Date
- 20. 1.2015 18:30:22
17. 9.2018 18:22:23
- Source
- Aslib journal of information management. 67(2015) no.1, S.27-54
-
Campanario, J.M.: Large increases and decreases in journal impact factors in only one year : the effect of journal self-citations (2011)
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- Date
- 22. 1.2011 12:53:00
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.230-235
-
Ding, Y.: Applying weighted PageRank to author citation networks (2011)
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- Date
- 22. 1.2011 13:02:21
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.236-245
-
Vieira, E.S.; Cabral, J.A.S.; Gomes, J.A.N.F.: Definition of a model based on bibliometric indicators for assessing applicants to academic positions (2014)
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- Date
- 18. 3.2014 18:22:21
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.3, S.560-577
-
Crespo, J.A.; Herranz, N.; Li, Y.; Ruiz-Castillo, J.: ¬The effect on citation inequality of differences in citation practices at the web of science subject category level (2014)
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- Abstract
- This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz-Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ?14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all-sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.6, S.1244-1256
-
Yan, E.: Finding knowledge paths among scientific disciplines (2014)
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- Date
- 26.10.2014 20:22:22
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.11, S.2331-2347
-
Jonkers, K.; Derrick, G.E.: ¬The bibliometric bandwagon : characteristics of bibliometric articles outside the field literature (2012)
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- Content
- Erratum dazu in: JASIST 63(2012) no.6, S.1280.
- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.4, S.829-836
-
Chang, K.-C.; Zhou, W.; Zhang, S.; Yuan, C,-C.: Threshold effects of the patent H-index in the relationship between patent citations and market value (2015)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2697-2703
-
Haustein, S.; Bowman, T.D.; Holmberg, K.; Tsou, A.; Sugimoto, C.R.; Larivière, V.: Tweets as impact indicators : Examining the implications of automated "bot" accounts on Twitter (2016)
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- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.1, S.232-238
