-
Kim, J.: Describing and predicting information-seeking behavior on the Web (2009)
0.00
0.0027544359 = product of:
0.041316535 = sum of:
0.041316535 = sum of:
0.017759778 = weight(_text_:information in 2747) [ClassicSimilarity], result of:
0.017759778 = score(doc=2747,freq=18.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.34911853 = fieldWeight in 2747, product of:
4.2426405 = tf(freq=18.0), with freq of:
18.0 = termFreq=18.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=2747)
0.023556758 = weight(_text_:22 in 2747) [ClassicSimilarity], result of:
0.023556758 = score(doc=2747,freq=2.0), product of:
0.101476215 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.028978055 = queryNorm
0.23214069 = fieldWeight in 2747, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=2747)
0.06666667 = coord(1/15)
- Abstract
- This study focuses on the task as a fundamental factor in the context of information seeking. The purpose of the study is to characterize kinds of tasks and to examine how different kinds of task give rise to different kinds of information-seeking behavior on the Web. For this, a model for information-seeking behavior was used employing dimensions of information-seeking strategies (ISS), which are based on several behavioral dimensions. The analysis of strategies was based on data collected through an experiment designed to observe users' behaviors. Three tasks were assigned to 30 graduate students and data were collected using questionnaires, search logs, and interviews. The qualitative and quantitative analysis of the data identified 14 distinct information-seeking strategies. The analysis showed significant differences in the frequencies and patterns of ISS employed between three tasks. The results of the study are intended to facilitate the development of task-based information-seeking models and to further suggest Web information system designs that support the user's diverse tasks.
- Date
- 22. 3.2009 18:54:15
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.679-693
-
Kang, I.-S.; Na, S.-H.; Kim, J.; Lee, J.-H.: Cluster-based patent retrieval (2007)
0.00
3.9466174E-4 = product of:
0.005919926 = sum of:
0.005919926 = product of:
0.011839852 = sum of:
0.011839852 = weight(_text_:information in 930) [ClassicSimilarity], result of:
0.011839852 = score(doc=930,freq=8.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.23274569 = fieldWeight in 930, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=930)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Abstract
- Through the recent NTCIR workshops, patent retrieval casts many challenging issues to information retrieval community. Unlike newspaper articles, patent documents are very long and well structured. These characteristics raise the necessity to reassess existing retrieval techniques that have been mainly developed for structure-less and short documents such as newspapers. This study investigates cluster-based retrieval in the context of invalidity search task of patent retrieval. Cluster-based retrieval assumes that clusters would provide additional evidence to match user's information need. Thus far, cluster-based retrieval approaches have relied on automatically-created clusters. Fortunately, all patents have manually-assigned cluster information, international patent classification codes. International patent classification is a standard taxonomy for classifying patents, and has currently about 69,000 nodes which are organized into a five-level hierarchical system. Thus, patent documents could provide the best test bed to develop and evaluate cluster-based retrieval techniques. Experiments using the NTCIR-4 patent collection showed that the cluster-based language model could be helpful to improving the cluster-less baseline language model.
- Source
- Information processing and management. 43(2007) no.5, S.1173-1182
-
Kim, J.; Diesner, J.: Coauthorship networks : a directed network approach considering the order and number of coauthors (2015)
0.00
2.848226E-4 = product of:
0.004272339 = sum of:
0.004272339 = product of:
0.008544678 = sum of:
0.008544678 = weight(_text_:information in 2346) [ClassicSimilarity], result of:
0.008544678 = score(doc=2346,freq=6.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.16796975 = fieldWeight in 2346, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=2346)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Abstract
- In many scientific fields, the order of coauthors on a paper conveys information about each individual's contribution to a piece of joint work. We argue that in prior network analyses of coauthorship networks, the information on ordering has been insufficiently considered because ties between authors are typically symmetrized. This is basically the same as assuming that each coauthor has contributed equally to a paper. We introduce a solution to this problem by adopting a coauthorship credit allocation model proposed by Kim and Diesner (2014), which in its core conceptualizes coauthoring as a directed, weighted, and self-looped network. We test and validate our application of the adopted framework based on a sample data of 861 authors who have published in the journal Psychometrika. The results suggest that this novel sociometric approach can complement traditional measures based on undirected networks and expand insights into coauthoring patterns such as the hierarchy of collaboration among scholars. As another form of validation, we also show how our approach accurately detects prominent scholars in the Psychometric Society affiliated with the journal.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2685-2696
-
Kim, J.; Thomas, P.; Sankaranarayana, R.; Gedeon, T.; Yoon, H.-J.: Eye-tracking analysis of user behavior and performance in web search on large and small screens (2015)
0.00
2.3255666E-4 = product of:
0.0034883497 = sum of:
0.0034883497 = product of:
0.0069766995 = sum of:
0.0069766995 = weight(_text_:information in 1666) [ClassicSimilarity], result of:
0.0069766995 = score(doc=1666,freq=4.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.13714671 = fieldWeight in 1666, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=1666)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Abstract
- In recent years, searching the web on mobile devices has become enormously popular. Because mobile devices have relatively small screens and show fewer search results, search behavior with mobile devices may be different from that with desktops or laptops. Therefore, examining these differences may suggest better, more efficient designs for mobile search engines. In this experiment, we use eye tracking to explore user behavior and performance. We analyze web searches with 2 task types on 2 differently sized screens: one for a desktop and the other for a mobile device. In addition, we examine the relationships between search performance and several search behaviors to allow further investigation of the differences engendered by the screens. We found that users have more difficulty extracting information from search results pages on the smaller screens, although they exhibit less eye movement as a result of an infrequent use of the scroll function. However, in terms of search performance, our findings suggest that there is no significant difference between the 2 screens in time spent on search results pages and the accuracy of finding answers. This suggests several possible ideas for the presentation design of search results pages on small devices.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.3, S.526-544
-
Yakel, E.; Kim, J.: Adoption and diffusion of Encoded Archival Description (2005)
0.00
1.9733087E-4 = product of:
0.002959963 = sum of:
0.002959963 = product of:
0.005919926 = sum of:
0.005919926 = weight(_text_:information in 4812) [ClassicSimilarity], result of:
0.005919926 = score(doc=4812,freq=2.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.116372846 = fieldWeight in 4812, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=4812)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Source
- Journal of the American Society for Information Science and Technology. 56(2005) no.13, S.1427-1437
-
Kim, J.: Faculty self-archiving : motivations and barriers (2010)
0.00
1.6444239E-4 = product of:
0.0024666358 = sum of:
0.0024666358 = product of:
0.0049332716 = sum of:
0.0049332716 = weight(_text_:information in 3989) [ClassicSimilarity], result of:
0.0049332716 = score(doc=3989,freq=2.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.09697737 = fieldWeight in 3989, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=3989)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.9, S.1909-1922
-
Kim, J.; Diesner, J.: Distortive effects of initial-based name disambiguation on measurements of large-scale coauthorship networks (2016)
0.00
1.6444239E-4 = product of:
0.0024666358 = sum of:
0.0024666358 = product of:
0.0049332716 = sum of:
0.0049332716 = weight(_text_:information in 2936) [ClassicSimilarity], result of:
0.0049332716 = score(doc=2936,freq=2.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.09697737 = fieldWeight in 2936, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=2936)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.6, S.1446-1461
-
Kim, J.; Thomas, P.; Sankaranarayana, R.; Gedeon, T.; Yoon, H.-J.: Understanding eye movements on mobile devices for better presentation of search results (2016)
0.00
1.6444239E-4 = product of:
0.0024666358 = sum of:
0.0024666358 = product of:
0.0049332716 = sum of:
0.0049332716 = weight(_text_:information in 3148) [ClassicSimilarity], result of:
0.0049332716 = score(doc=3148,freq=2.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.09697737 = fieldWeight in 3148, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=3148)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.11, S.2607-2619
-
Kim, J.: Author-based analysis of conference versus journal publication in computer science (2019)
0.00
1.6444239E-4 = product of:
0.0024666358 = sum of:
0.0024666358 = product of:
0.0049332716 = sum of:
0.0049332716 = weight(_text_:information in 4678) [ClassicSimilarity], result of:
0.0049332716 = score(doc=4678,freq=2.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.09697737 = fieldWeight in 4678, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=4678)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Source
- Journal of the Association for Information Science and Technology. 70(2019) no.1, S.71-82
-
Kim, J.: Scale-free collaboration networks : an author name disambiguation perspective (2019)
0.00
1.6444239E-4 = product of:
0.0024666358 = sum of:
0.0024666358 = product of:
0.0049332716 = sum of:
0.0049332716 = weight(_text_:information in 5297) [ClassicSimilarity], result of:
0.0049332716 = score(doc=5297,freq=2.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.09697737 = fieldWeight in 5297, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=5297)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Source
- Journal of the Association for Information Science and Technology. 70(2019) no.7, S.685-700
-
Kim, J.; Kim, J.; Owen-Smith, J.: Ethnicity-based name partitioning for author name disambiguation using supervised machine learning (2021)
0.00
1.6444239E-4 = product of:
0.0024666358 = sum of:
0.0024666358 = product of:
0.0049332716 = sum of:
0.0049332716 = weight(_text_:information in 311) [ClassicSimilarity], result of:
0.0049332716 = score(doc=311,freq=2.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.09697737 = fieldWeight in 311, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=311)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Source
- Journal of the Association for Information Science and Technology. 72(2021) no.8, S.979-994
-
Walsh, J.A.; Cobb, P.J.; Fremery, W. de; Golub, K.; Keah, H.; Kim, J.; Kiplang'at, J.; Liu, Y.-H.; Mahony, S.; Oh, S.G.; Sula, C.A.; Underwood, T.; Wang, X.: Digital humanities in the iSchool (2022)
0.00
1.6444239E-4 = product of:
0.0024666358 = sum of:
0.0024666358 = product of:
0.0049332716 = sum of:
0.0049332716 = weight(_text_:information in 463) [ClassicSimilarity], result of:
0.0049332716 = score(doc=463,freq=2.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.09697737 = fieldWeight in 463, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=463)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.2, S.188-203
