-
Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015)
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- Abstract
- Purpose - The purpose of this paper is to analyse the global scientific outputs of ontology research, an important emerging discipline that has huge potential to improve information understanding, organization, and management. Design/methodology/approach - This study collected literature published during 1900-2012 from the Web of Science database. The bibliometric analysis was performed from authorial, institutional, national, spatiotemporal, and topical aspects. Basic statistical analysis, visualization of geographic distribution, co-word analysis, and a new index were applied to the selected data. Findings - Characteristics of publication outputs suggested that ontology research has entered into the soaring stage, along with increased participation and collaboration. The authors identified the leading authors, institutions, nations, and articles in ontology research. Authors were more from North America, Europe, and East Asia. The USA took the lead, while China grew fastest. Four major categories of frequently used keywords were identified: applications in Semantic Web, applications in bioinformatics, philosophy theories, and common supporting technology. Semantic Web research played a core role, and gene ontology study was well-developed. The study focus of ontology has shifted from philosophy to information science. Originality/value - This is the first study to quantify global research patterns and trends in ontology, which might provide a potential guide for the future research. The new index provides an alternative way to evaluate the multidisciplinary influence of researchers.
- Date
- 20. 1.2015 18:30:22
17. 9.2018 18:22:23
-
Zheng, R.; Li, J.; Chen, H.; Huang, Z.: ¬A framework for authorship identification of online messages : writing-style features and classification techniques (2006)
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- Abstract
- With the rapid proliferation of Internet technologies and applications, misuse of online messages for inappropriate or illegal purposes has become a major concern for society. The anonymous nature of online-message distribution makes identity tracing a critical problem. We developed a framework for authorship identification of online messages to address the identity-tracing problem. In this framework, four types of writing-style features (lexical, syntactic, structural, and content-specific features) are extracted and inductive learning algorithms are used to build feature-based classification models to identify authorship of online messages. To examine this framework, we conducted experiments on English and Chinese online-newsgroup messages. We compared the discriminating power of the four types of features and of three classification techniques: decision trees, backpropagation neural networks, and support vector machines. The experimental results showed that the proposed approach was able to identify authors of online messages with satisfactory accuracy of 70 to 95%. All four types of message features contributed to discriminating authors of online messages. Support vector machines outperformed the other two classification techniques in our experiments. The high performance we achieved for both the English and Chinese datasets showed the potential of this approach in a multiple-language context.
- Date
- 22. 7.2006 16:14:37
- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.378-393
-
Li, J.; Wu, G.: Characteristics of reference transactions : challenges to librarian's roles (1998)
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- Abstract
- Reports results of a study to analyze the nature of reference services and reference desk transactions. 2 reference librarians, one from South Alabama University, Biomedical Library and the other from the Shiffman Medical Library, Wayne State University, Michigan, recorded reference transactions while they staffed the reference desks at their respective institutions from May to October 1996. 2 types of data were collected; types of tools or sources used to provide answers to reference queries; and instruction provided, from the reference desk, on different types of application
- Date
- 16. 3.1999 9:17:29
- Footnote
- Article included in a special section devoted to work undertaken as part of the University of Iowa Digital Library Project
- Source
- Bulletin of the Medical Library Association. 86(1998) no.4, S.610-612
-
Lin, X.; Li, J.; Zhou, X.: Theme creation for digital collections (2008)
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- Source
- Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
-
Li, J.; Zhang, P.; Cao, J.: External concept support for group support systems through Web mining (2009)
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- Abstract
- External information plays an important role in group decision-making processes, yet research about external information support for Group Support Systems (GSS) has been lacking. In this study, we propose an approach to build a concept space to provide external concept support for GSS users. Built on a Web mining algorithm, the approach can mine a concept space from the Web and retrieve related concepts from the concept space based on users' comments in a real-time manner. We conduct two experiments to evaluate the quality of the proposed approach and the effectiveness of the external concept support provided by this approach. The experiment results indicate that the concept space mined from the Web contained qualified concepts to stimulate divergent thinking. The results also demonstrate that external concept support in GSS greatly enhanced group productivity for idea generation tasks.
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.5, S.1057-1070
-
Lin, N.; Li, D.; Ding, Y.; He, B.; Qin, Z.; Tang, J.; Li, J.; Dong, T.: ¬The dynamic features of Delicious, Flickr, and YouTube (2012)
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- Abstract
- This article investigates the dynamic features of social tagging vocabularies in Delicious, Flickr, and YouTube from 2003 to 2008. Three algorithms are designed to study the macro- and micro-tag growth as well as the dynamics of taggers' activities, respectively. Moreover, we propose a Tagger Tag Resource Latent Dirichlet Allocation (TTR-LDA) model to explore the evolution of topics emerging from those social vocabularies. Our results show that (a) at the macro level, tag growth in all the three tagging systems obeys power law distribution with exponents lower than 1; at the micro level, the tag growth of popular resources in all three tagging systems follows a similar power law distribution; (b) the exponents of tag growth vary in different evolving stages of resources; (c) the growth of number of taggers associated with different popular resources presents a feature of convergence over time; (d) the active level of taggers has a positive correlation with the macro-tag growth of different tagging systems; and (e) some topics evolve into several subtopics over time while others experience relatively stable stages in which their contents do not change much, and certain groups of taggers continue their interests in them.
- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.1, S.139-162
-
Zhao, S.X.; Zhang, P.L.; Li, J.; Tan, A.M.; Ye, F.Y.: Abstracting the core subnet of weighted networks based on link strengths (2014)
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- Abstract
- Most measures of networks are based on the nodes, although links are also elementary units in networks and represent interesting social or physical connections. In this work we suggest an option for exploring networks, called the h-strength, with explicit focus on links and their strengths. The h-strength and its extensions can naturally simplify a complex network to a small and concise subnetwork (h-subnet) but retains the most important links with its core structure. Its applications in 2 typical information networks, the paper cocitation network of a topic (the h-index) and 5 scientific collaboration networks in the field of "water resources," suggest that h-strength and its extensions could be a useful choice for abstracting, simplifying, and visualizing a complex network. Moreover, we observe that the 2 informetric models, the Glänzel-Schubert model and the Hirsch model, roughly hold in the context of the h-strength for the collaboration networks.
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.5, S.984-994
-
Li, J.; Zhang, P.; Song, D.; Wu, Y.: Understanding an enriched multidimensional user relevance model by analyzing query logs (2017)
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- Abstract
- Modeling multidimensional relevance in information retrieval (IR) has attracted much attention in recent years. However, most existing studies are conducted through relatively small-scale user studies, which may not reflect a real-world and natural search scenario. In this article, we propose to study the multidimensional user relevance model (MURM) on large scale query logs, which record users' various search behaviors (e.g., query reformulations, clicks and dwelling time, etc.) in natural search settings. We advance an existing MURM model (including five dimensions: topicality, novelty, reliability, understandability, and scope) by providing two additional dimensions, that is, interest and habit. The two new dimensions represent personalized relevance judgment on retrieved documents. Further, for each dimension in the enriched MURM model, a set of computable features are formulated. By conducting extensive document ranking experiments on Bing's query logs and TREC session Track data, we systematically investigated the impact of each dimension on retrieval performance and gained a series of insightful findings which may bring benefits for the design of future IR systems.
- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.12, S.2743-2754
-
Shi, D.; Rousseau, R.; Yang, L.; Li, J.: ¬A journal's impact factor is influenced by changes in publication delays of citing journals (2017)
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- Abstract
- In this article we describe another problem with journal impact factors by showing that one journal's impact factor is dependent on other journals' publication delays. The proposed theoretical model predicts a monotonically decreasing function of the impact factor as a function of publication delay, on condition that the citation curve of the journal is monotone increasing during the publication window used in the calculation of the journal impact factor; otherwise, this function has a reversed U shape. Our findings based on simulations are verified by examining three journals in the information sciences: the Journal of Informetrics, Scientometrics, and the Journal of the Association for Information Science and Technology.
- Date
- 16.11.2017 13:29:52
- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.3, S.780-789
-
Li, J.; Shi, D.: Sleeping beauties in genius work : when were they awakened? (2016)
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- Abstract
- "Genius work," proposed by Avramescu, refers to scientific articles whose citations grow exponentially in an extended period, for example, over 50 years. Such articles were defined as "sleeping beauties" by van Raan, who quantitatively studied the phenomenon of delayed recognition. However, the criteria adopted by van Raan at times are not applicable and may confer recognition prematurely. To revise such deficiencies, this paper proposes two new criteria, which are applicable (but not limited) to exponential citation curves. We searched for genius work among articles of Nobel Prize laureates during the period of 1901-2012 on the Web of Science, finding 25 articles of genius work out of 21,438 papers including 10 (by van Raan's criteria) sleeping beauties and 15 nonsleeping-beauties. By our new criteria, two findings were obtained through empirical analysis: (a) the awakening periods for genius work depend on the increase rate b in the exponential function, and (b) lower b leads to a longer sleeping period.
- Date
- 22. 1.2016 14:13:32
- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.2, S.432-440
-
Zhang, C.; Zeng, D.; Li, J.; Wang, F.-Y.; Zuo, W.: Sentiment analysis of Chinese documents : from sentence to document level (2009)
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- Date
- 2. 2.2010 19:29:56
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2474-2487
-
Xie, Z.; Ouyang, Z.; Li, J.; Dong, E.: Modelling transition phenomena of scientific coauthorship networks (2018)
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- Date
- 14. 1.2018 17:03:29
- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.2, S.305-317
-
Min, C.; Ding, Y.; Li, J.; Bu, Y.; Pei, L.; Sun, J.: Innovation or imitation : the diffusion of citations (2018)
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- Date
- 29. 9.2018 13:24:10
- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.10, S.1271-1282
-
Lancaster, F.W.; Li, J.: ¬The law of constant accessibility of information (1988/89)
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- Source
- Bulletin of the American Society for Information Science. 15(1988/89), S.24-25
-
Liu, X.; Bu, Y.; Li, M.; Li, J.: Monodisciplinary collaboration disrupts science more than multidisciplinary collaboration (2024)
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- Abstract
- Collaboration across disciplines is a critical form of scientific collaboration to solve complex problems and make innovative contributions. This study focuses on the association between multidisciplinary collaboration measured by coauthorship in publications and the disruption of publications measured by the Disruption (D) index. We used authors' affiliations as a proxy of the disciplines to which they belong and categorized an article into multidisciplinary collaboration or monodisciplinary collaboration. The D index quantifies the extent to which a study disrupts its predecessors. We selected 13 journals that publish articles in six disciplines from the Microsoft Academic Graph (MAG) database and then constructed regression models with fixed effects and estimated the relationship between the variables. The findings show that articles with monodisciplinary collaboration are more disruptive than those with multidisciplinary collaboration. Furthermore, we uncovered the mechanism of how monodisciplinary collaboration disrupts science more than multidisciplinary collaboration by exploring the references of the sampled publications.
- Source
- Journal of the Association for Information Science and Technology. 75(2023) no.1, S.59-78
-
Wu, S.; Li, J.; Zeng, X.; Bi, Y.: Adaptive data fusion methods in information retrieval (2014)
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- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.10, S.2048-2061
-
Li, J.; Zhang, Z.; Li, X.; Chen, H.: Kernel-based learning for biomedical relation extraction (2008)
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- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.5, S.756-769
-
Li, J.; Sun, A.; Xing, Z.: To do or not to do : distill crowdsourced negative caveats to augment api documentation (2018)
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- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.12, S.1460-1475
-
Du, Q.; Li, J.; Du, Y.; Wang, G.A.; Fan, W.: Predicting crowdfunding project success based on backers' language preferences (2021)
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- Source
- Journal of the Association for Information Science and Technology. 72(2021) no.12, S.1558-1574
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Zhang, Y.; Zhang, C.; Li, J.: Joint modeling of characters, words, and conversation contexts for microblog keyphrase extraction (2020)
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- Source
- Journal of the Association for Information Science and Technology. 71(2020) no.5, S.553-567
