Search (19 results, page 1 of 1)

Ding, Y.; Chowdhury, G.; Foo, S.: Organsising keywords in a Web search environment : a methodology based on co-word analysis (2000) 0.07

0.07102625 = product of:
  0.1420525 = sum of:
    0.055176124 = weight(_text_:wide in 105) [ClassicSimilarity], result of:
      0.055176124 = score(doc=105,freq=2.0), product of:
        0.18785246 = queryWeight, product of:
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.042397358 = queryNorm
        0.29372054 = fieldWeight in 105, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.046875 = fieldNorm(doc=105)
    0.042333104 = weight(_text_:web in 105) [ClassicSimilarity], result of:
      0.042333104 = score(doc=105,freq=4.0), product of:
        0.13836423 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.042397358 = queryNorm
        0.3059541 = fieldWeight in 105, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.046875 = fieldNorm(doc=105)
    0.04454327 = weight(_text_:retrieval in 105) [ClassicSimilarity], result of:
      0.04454327 = score(doc=105,freq=6.0), product of:
        0.12824841 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.042397358 = queryNorm
        0.34732026 = fieldWeight in 105, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=105)
  0.5 = coord(3/6)

Abstract: The rapid development of the Internet and World Wide Web has caused some critical problem for information retrieval. Researchers have made several attempts to solve these problems. Thesauri and subject heading lists as traditional information retrieval tools have been criticised for their efficiency to tackle these newly emerging problems. This paper proposes an information retrieval tool generated by cocitation analysis, comprising keyword clusters with relationships based on the co-occurrences of keywords in the literature. Such a tool can play the role of an associative thesaurus that can provide information about the keywords in a domain that might be useful for information searching and query expansion

Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.04

0.03916477 = product of:
  0.07832954 = sum of:
    0.03492303 = weight(_text_:web in 4188) [ClassicSimilarity], result of:
      0.03492303 = score(doc=4188,freq=2.0), product of:
        0.13836423 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.042397358 = queryNorm
        0.25239927 = fieldWeight in 4188, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.0546875 = fieldNorm(doc=4188)
    0.030003246 = weight(_text_:retrieval in 4188) [ClassicSimilarity], result of:
      0.030003246 = score(doc=4188,freq=2.0), product of:
        0.12824841 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.042397358 = queryNorm
        0.23394634 = fieldWeight in 4188, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0546875 = fieldNorm(doc=4188)
    0.013403265 = product of:
      0.040209793 = sum of:
        0.040209793 = weight(_text_:22 in 4188) [ClassicSimilarity], result of:
          0.040209793 = score(doc=4188,freq=2.0), product of:
            0.14846832 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.042397358 = queryNorm
            0.2708308 = fieldWeight in 4188, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4188)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)

Abstract: This article aims to identify whether different weighted PageRank algorithms can be applied to author citation networks to measure the popularity and prestige of a scholar from a citation perspective. Information retrieval (IR) was selected as a test field and data from 1956-2008 were collected from Web of Science. Weighted PageRank with citation and publication as weighted vectors were calculated on author citation networks. The results indicate that both popularity rank and prestige rank were highly correlated with the weighted PageRank. Principal component analysis was conducted to detect relationships among these different measures. For capturing prize winners within the IR field, prestige rank outperformed all the other measures
Date: 22. 1.2011 13:02:21

Ding, Y.; Jacob, E.K.; Zhang, Z.; Foo, S.; Yan, E.; George, N.L.; Guo, L.: Perspectives on social tagging (2009) 0.04

0.038348056 = product of:
  0.11504417 = sum of:
    0.055176124 = weight(_text_:wide in 3290) [ClassicSimilarity], result of:
      0.055176124 = score(doc=3290,freq=2.0), product of:
        0.18785246 = queryWeight, product of:
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.042397358 = queryNorm
        0.29372054 = fieldWeight in 3290, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.046875 = fieldNorm(doc=3290)
    0.059868045 = weight(_text_:web in 3290) [ClassicSimilarity], result of:
      0.059868045 = score(doc=3290,freq=8.0), product of:
        0.13836423 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.042397358 = queryNorm
        0.43268442 = fieldWeight in 3290, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.046875 = fieldNorm(doc=3290)
  0.33333334 = coord(2/6)

Abstract: Social tagging is one of the major phenomena transforming the World Wide Web from a static platform into an actively shared information space. This paper addresses various aspects of social tagging, including different views on the nature of social tagging, how to make use of social tags, and how to bridge social tagging with other Web functionalities; it discusses the use of facets to facilitate browsing and searching of tagging data; and it presents an analogy between bibliometrics and tagometrics, arguing that established bibliometric methodologies can be applied to analyze tagging behavior on the Web. Based on the Upper Tag Ontology (UTO), a Web crawler was built to harvest tag data from Delicious, Flickr, and YouTube in September 2007. In total, 1.8 million objects, including bookmarks, photos, and videos, 3.1 million taggers, and 12.1 million tags were collected and analyzed. Some tagging patterns and variations are identified and discussed.

Klein, M.; Ding, Y.; Fensel, D.; Omelayenko, B.: Ontology management : storing, aligning and maintaining ontologies (2004) 0.02
```
0.017794952 = product of:
  0.05338485 = sum of:
    0.04462301 = weight(_text_:web in 4402) [ClassicSimilarity], result of:
      0.04462301 = score(doc=4402,freq=10.0), product of:
        0.13836423 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.042397358 = queryNorm
        0.32250395 = fieldWeight in 4402, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.03125 = fieldNorm(doc=4402)
    0.008761841 = product of:
      0.026285522 = sum of:
        0.026285522 = weight(_text_:system in 4402) [ClassicSimilarity], result of:
          0.026285522 = score(doc=4402,freq=4.0), product of:
            0.13353272 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.042397358 = queryNorm
            0.19684705 = fieldWeight in 4402, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.03125 = fieldNorm(doc=4402)
      0.33333334 = coord(1/3)
  0.33333334 = coord(2/6)
```
Abstract

Ontologies need to be stored, sometimes aligned and their evolution needs to be managed. All these tasks together are called ontology management. Alignment is a central task in ontology re-use. Re-use of existing ontologies often requires considerable effort: the ontologies either need to be integrated, which means that they are merged into one new ontology, or the ontologies can be kept separate. In both cases, the ontologies have to be aligned, which means that they have to be brought into mutual agreement. The problems that underlie the difficulties in integrating and aligning are the mismatches that may exist between separate ontologies. Ontologies can differ at the language level, which can mean that they are represented in a different syntax, or that the expressiveness of the ontology language is dissimilar. Ontologies also can have mismatches at the model level, for example, in the paradigm, or modelling style. Ontology alignment is very relevant in a Semantic Web context. The Semantic Web will provide us with a lot of freely accessible domain specific ontologies. To form a real web of semantics - which will allow computers to combine and infer implicit knowledge - those separate ontologies should be aligned and linked.
Support for evolving ontologies is required in almost all situations where ontologies are used in real-world applications. In those cases, ontologies are often developed by several persons and will continue to evolve over time, because of changes in the real world, adaptations to different tasks, or alignments to other ontologies. To prevent that such changes will invalidate existing usage, a change management methodology is needed. This involves advanced versioning methods for the development and the maintenance of ontologies, but also configuration management, that takes care of the identification, relations and interpretation of ontology versions. All these aspects come together in integrated ontology library systems. When the number of different ontologies is increasing, the task of storing, maintaining and re-organizing them to secure the successful re-use of ontologies is challenging. Ontology library systems can help in the grouping and reorganizing ontologies for further re-use, integration, maintenance, mapping and versioning. Basically, a library system offers various functions for managing, adapting and standardizing groups of ontologies. Such integrated systems are a requirement for the Semantic Web to grow further and scale up. In this chapter, we describe a number of results with respect to the above mentioned areas. We start with a description of the alignment task and show a meta-ontology that is developed to specify the mappings. Then, we discuss the problems that are caused by evolving ontologies and describe two important elements of a change management methodology. Finally, in Section 4.4 we survey existing library systems and formulate a wish-list of features of an ontology library system.

Source

Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a

Ding, Y.: ¬A review of ontologies with the Semantic Web in view (2001) 0.02

0.016462874 = product of:
  0.09877724 = sum of:
    0.09877724 = weight(_text_:web in 4152) [ClassicSimilarity], result of:
      0.09877724 = score(doc=4152,freq=4.0), product of:
        0.13836423 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.042397358 = queryNorm
        0.71389294 = fieldWeight in 4152, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.109375 = fieldNorm(doc=4152)
  0.16666667 = coord(1/6)

Theme: Semantic Web

Ding, Y.: Visualization of intellectual structure in information retrieval : author cocitation analysis (1998) 0.01
```
0.010001082 = product of:
  0.06000649 = sum of:
    0.06000649 = weight(_text_:retrieval in 2792) [ClassicSimilarity], result of:
      0.06000649 = score(doc=2792,freq=8.0), product of:
        0.12824841 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.042397358 = queryNorm
        0.46789268 = fieldWeight in 2792, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2792)
  0.16666667 = coord(1/6)
```
Abstract

Reports results of a cocitation analysis study from the international retrieval research field from 1987 to 1997. Data was taken from Social SciSearch, via Dialog, and the top 40 authors were submitted to author cocitation analysis to yield the intellectual structure of information retrieval. The resulting multidimensional scaling map revealed: identifiable author groups for information retrieval; location of these groups with respect to each other; extend of centrality and peripherality of authors within groups, proximities of authors within groups and across group boundaries; and the meaning of the axes of the map. Factor analysis was used to reveal the extent of the authors' research areas and statistical routines included: ALSCAL; clustering analysis and factor analysis
Ding, Y.; Jacob, E.K.; Fried, M.; Toma, I.; Yan, E.; Foo, S.; Milojevicacute, S.: Upper tag ontology for integrating social tagging data (2010) 0.01
```
0.008641209 = product of:
  0.051847253 = sum of:
    0.051847253 = weight(_text_:web in 3421) [ClassicSimilarity], result of:
      0.051847253 = score(doc=3421,freq=6.0), product of:
        0.13836423 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.042397358 = queryNorm
        0.37471575 = fieldWeight in 3421, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.046875 = fieldNorm(doc=3421)
  0.16666667 = coord(1/6)
```
Abstract

Data integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube).

Ding, Y.; Chowdhury, G.C.; Foo, S.: Bibliometric cartography of information retrieval research by using co-word analysis (2001) 0.01

0.008572357 = product of:
  0.051434137 = sum of:
    0.051434137 = weight(_text_:retrieval in 6487) [ClassicSimilarity], result of:
      0.051434137 = score(doc=6487,freq=2.0), product of:
        0.12824841 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.042397358 = queryNorm
        0.40105087 = fieldWeight in 6487, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.09375 = fieldNorm(doc=6487)
  0.16666667 = coord(1/6)

Ding, Y.; Chowdhury, G.C.; Foo, S.: Incorporating the results of co-word analyses to increase search variety for information retrieval (2000) 0.01

0.008572357 = product of:
  0.051434137 = sum of:
    0.051434137 = weight(_text_:retrieval in 6328) [ClassicSimilarity], result of:
      0.051434137 = score(doc=6328,freq=2.0), product of:
        0.12824841 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.042397358 = queryNorm
        0.40105087 = fieldWeight in 6328, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.09375 = fieldNorm(doc=6328)
  0.16666667 = coord(1/6)

Hu, B.; Dong, X.; Zhang, C.; Bowman, T.D.; Ding, Y.; Milojevic, S.; Ni, C.; Yan, E.; Larivière, V.: ¬A lead-lag analysis of the topic evolution patterns for preprints and publications (2015) 0.00
```
0.0049890038 = product of:
  0.029934023 = sum of:
    0.029934023 = weight(_text_:web in 2337) [ClassicSimilarity], result of:
      0.029934023 = score(doc=2337,freq=2.0), product of:
        0.13836423 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.042397358 = queryNorm
        0.21634221 = fieldWeight in 2337, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.046875 = fieldNorm(doc=2337)
  0.16666667 = coord(1/6)
```
Abstract

This study applied LDA (latent Dirichlet allocation) and regression analysis to conduct a lead-lag analysis to identify different topic evolution patterns between preprints and papers from arXiv and the Web of Science (WoS) in astrophysics over the last 20 years (1992-2011). Fifty topics in arXiv and WoS were generated using an LDA algorithm and then regression models were used to explain 4 types of topic growth patterns. Based on the slopes of the fitted equation curves, the paper redefines the topic trends and popularity. Results show that arXiv and WoS share similar topics in a given domain, but differ in evolution trends. Topics in WoS lose their popularity much earlier and their durations of popularity are shorter than those in arXiv. This work demonstrates that open access preprints have stronger growth tendency as compared to traditional printed publications.
Ding, Y.; Yan, E.; Frazho, A.; Caverlee, J.: PageRank for ranking authors in co-citation networks (2009) 0.00
```
0.0042861784 = product of:
  0.025717068 = sum of:
    0.025717068 = weight(_text_:retrieval in 3161) [ClassicSimilarity], result of:
      0.025717068 = score(doc=3161,freq=2.0), product of:
        0.12824841 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.042397358 = queryNorm
        0.20052543 = fieldWeight in 3161, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=3161)
  0.16666667 = coord(1/6)
```
Abstract

This paper studies how varied damping factors in the PageRank algorithm influence the ranking of authors and proposes weighted PageRank algorithms. We selected the 108 most highly cited authors in the information retrieval (IR) area from the 1970s to 2008 to form the author co-citation network. We calculated the ranks of these 108 authors based on PageRank with the damping factor ranging from 0.05 to 0.95. In order to test the relationship between different measures, we compared PageRank and weighted PageRank results with the citation ranking, h-index, and centrality measures. We found that in our author co-citation network, citation rank is highly correlated with PageRank with different damping factors and also with different weighted PageRank algorithms; citation rank and PageRank are not significantly correlated with centrality measures; and h-index rank does not significantly correlate with centrality measures but does significantly correlate with other measures. The key factors that have impact on the PageRank of authors in the author co-citation network are being co-cited with important authors.
Ding, Y.: Topic-based PageRank on author cocitation networks (2011) 0.00
```
0.0042861784 = product of:
  0.025717068 = sum of:
    0.025717068 = weight(_text_:retrieval in 4348) [ClassicSimilarity], result of:
      0.025717068 = score(doc=4348,freq=2.0), product of:
        0.12824841 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.042397358 = queryNorm
        0.20052543 = fieldWeight in 4348, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=4348)
  0.16666667 = coord(1/6)
```
Abstract

Ranking authors is vital for identifying a researcher's impact and standing within a scientific field. There are many different ranking methods (e.g., citations, publications, h-index, PageRank, and weighted PageRank), but most of them are topic-independent. This paper proposes topic-dependent ranks based on the combination of a topic model and a weighted PageRank algorithm. The author-conference-topic (ACT) model was used to extract topic distribution of individual authors. Two ways for combining the ACT model with the PageRank algorithm are proposed: simple combination (I_PR) or using a topic distribution as a weighted vector for PageRank (PR_t). Information retrieval was chosen as the test field and representative authors for different topics at different time phases were identified. Principal component analysis (PCA) was applied to analyze the ranking difference between I_PR and PR_t.
Sugimoto, C.R.; Li, D.; Russell, T.G.; Finlay, S.C.; Ding, Y.: ¬The shifting sands of disciplinary development : analyzing North American Library and Information Science dissertations using latent Dirichlet allocation (2011) 0.00
```
0.0035718149 = product of:
  0.02143089 = sum of:
    0.02143089 = weight(_text_:retrieval in 4143) [ClassicSimilarity], result of:
      0.02143089 = score(doc=4143,freq=2.0), product of:
        0.12824841 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.042397358 = queryNorm
        0.16710453 = fieldWeight in 4143, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4143)
  0.16666667 = coord(1/6)
```
Abstract

This work identifies changes in dominant topics in library and information science (LIS) over time, by analyzing the 3,121 doctoral dissertations completed between 1930 and 2009 at North American Library and Information Science programs. The authors utilize latent Dirichlet allocation (LDA) to identify latent topics diachronically and to identify representative dissertations of those topics. The findings indicate that the main topics in LIS have changed substantially from those in the initial period (1930-1969) to the present (2000-2009). However, some themes occurred in multiple periods, representing core areas of the field: library history occurred in the first two periods; citation analysis in the second and third periods; and information-seeking behavior in the fourth and last period. Two topics occurred in three of the five periods: information retrieval and information use. One of the notable changes in the topics was the diminishing use of the word library (and related terms). This has implications for the provision of doctoral education in LIS. This work is compared to other earlier analyses and provides validation for the use of LDA in topic analysis of a discipline.

Ding, Y.: Scholarly communication and bibliometrics : Part 1: The scholarly communication model: literature review (1998) 0.00

0.0032202217 = product of:
  0.01932133 = sum of:
    0.01932133 = product of:
      0.05796399 = sum of:
        0.05796399 = weight(_text_:29 in 3995) [ClassicSimilarity], result of:
          0.05796399 = score(doc=3995,freq=2.0), product of:
            0.14914064 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.042397358 = queryNorm
            0.38865322 = fieldWeight in 3995, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.078125 = fieldNorm(doc=3995)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Source: International forum on information and documentation. 23(1998) no.2, S.20-29

Song, M.; Kim, S.Y.; Zhang, G.; Ding, Y.; Chambers, T.: Productivity and influence in bioinformatics : a bibliometric analysis using PubMed central (2014) 0.00

0.001932133 = product of:
  0.011592798 = sum of:
    0.011592798 = product of:
      0.034778394 = sum of:
        0.034778394 = weight(_text_:29 in 1202) [ClassicSimilarity], result of:
          0.034778394 = score(doc=1202,freq=2.0), product of:
            0.14914064 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.042397358 = queryNorm
            0.23319192 = fieldWeight in 1202, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.046875 = fieldNorm(doc=1202)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date: 29. 1.2014 16:40:41

Ding, Y.; Zhang, G.; Chambers, T.; Song, M.; Wang, X.; Zhai, C.: Content-based citation analysis : the next generation of citation analysis (2014) 0.00

0.0019147521 = product of:
  0.011488512 = sum of:
    0.011488512 = product of:
      0.034465536 = sum of:
        0.034465536 = weight(_text_:22 in 1521) [ClassicSimilarity], result of:
          0.034465536 = score(doc=1521,freq=2.0), product of:
            0.14846832 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.042397358 = queryNorm
            0.23214069 = fieldWeight in 1521, 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=1521)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date: 22. 8.2014 16:52:04

Min, C.; Ding, Y.; Li, J.; Bu, Y.; Pei, L.; Sun, J.: Innovation or imitation : the diffusion of citations (2018) 0.00

0.0016101109 = product of:
  0.009660665 = sum of:
    0.009660665 = product of:
      0.028981995 = sum of:
        0.028981995 = weight(_text_:29 in 4445) [ClassicSimilarity], result of:
          0.028981995 = score(doc=4445,freq=2.0), product of:
            0.14914064 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.042397358 = queryNorm
            0.19432661 = fieldWeight in 4445, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4445)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date: 29. 9.2018 13:24:10

Liu, M.; Bu, Y.; Chen, C.; Xu, J.; Li, D.; Leng, Y.; Freeman, R.B.; Meyer, E.T.; Yoon, W.; Sung, M.; Jeong, M.; Lee, J.; Kang, J.; Min, C.; Zhai, Y.; Song, M.; Ding, Y.: Pandemics are catalysts of scientific novelty : evidence from COVID-19 (2022) 0.00
```
0.0016101109 = product of:
  0.009660665 = sum of:
    0.009660665 = product of:
      0.028981995 = sum of:
        0.028981995 = weight(_text_:29 in 633) [ClassicSimilarity], result of:
          0.028981995 = score(doc=633,freq=2.0), product of:
            0.14914064 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.042397358 = queryNorm
            0.19432661 = fieldWeight in 633, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.0390625 = fieldNorm(doc=633)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)
```
Abstract

Scientific novelty drives the efforts to invent new vaccines and solutions during the pandemic. First-time collaboration and international collaboration are two pivotal channels to expand teams' search activities for a broader scope of resources required to address the global challenge, which might facilitate the generation of novel ideas. Our analysis of 98,981 coronavirus papers suggests that scientific novelty measured by the BioBERT model that is pretrained on 29 million PubMed articles, and first-time collaboration increased after the outbreak of COVID-19, and international collaboration witnessed a sudden decrease. During COVID-19, papers with more first-time collaboration were found to be more novel and international collaboration did not hamper novelty as it had done in the normal periods. The findings suggest the necessity of reaching out for distant resources and the importance of maintaining a collaborative scientific community beyond nationalism during a pandemic.
Yan, E.; Ding, Y.; Sugimoto, C.R.: P-Rank: an indicator measuring prestige in heterogeneous scholarly networks (2011) 0.00
```
0.0015488893 = product of:
  0.0092933355 = sum of:
    0.0092933355 = product of:
      0.027880006 = sum of:
        0.027880006 = weight(_text_:system in 4349) [ClassicSimilarity], result of:
          0.027880006 = score(doc=4349,freq=2.0), product of:
            0.13353272 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.042397358 = queryNorm
            0.20878783 = fieldWeight in 4349, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.046875 = fieldNorm(doc=4349)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)
```
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.

Search (19 results, page 1 of 1)

Authors

Years

Types

Themes