Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 15. Juni 2019)
1Yi, D. (Hrsg.): Xie, Z. ; Ouyang, Z. ; Li, J. ; Dong, E.: Modelling transition phenomena of scientific coauthorship networks.
In: Journal of the Association for Information Science and Technology. 69(2018) no.2, S.305-317.
Abstract: In a range of scientific coauthorship networks, transitions emerge in degree distribution, in the correlation between degree and local clustering coefficient, etc. The existence of those transitions could be regarded because of the diversity in collaboration behaviors of scientific fields. A growing geometric hypergraph built on a cluster of concentric circles is proposed to model two specific collaboration behaviors, namely the behaviors of research team leaders and those of the other team members. The model successfully predicts the transitions, as well as many common features of coauthorship networks. Particularly, it realizes a process of deriving the complex "scale-free" property from the simple "yes/no" decisions. Moreover, it provides a reasonable explanation for the emergence of transitions with the difference of collaboration behaviors between leaders and other members. The difference emerges in the evolution of research teams, which synthetically addresses several specific factors of generating collaborations, namely the communications between research teams, academic impacts and homophily of authors.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23935/full.
2Min, C. ; Ding, Y. ; Li, J. ; Bu, Y. ; Pei, L. ; Sun, J.: Innovation or imitation : the diffusion of citations.
In: Journal of the Association for Information Science and Technology. 69(2018) no.10, S.1271-1282.
Abstract: Citations in scientific literature are important both for tracking the historical development of scientific ideas and for forecasting research trends. However, the diffusion mechanisms underlying the citation process remain poorly understood, despite the frequent and longstanding use of citation counts for assessment purposes within the scientific community. Here, we extend the study of citation dynamics to a more general diffusion process to understand how citation growth associates with different diffusion patterns. Using a classic diffusion model, we quantify and illustrate specific diffusion mechanisms which have been proven to exert a significant impact on the growth and decay of citation counts. Experiments reveal a positive relation between the "low p and low q" pattern and high scientific impact. A sharp citation peak produced by rapid change of citation counts, however, has a negative effect on future impact. In addition, we have suggested a simple indicator, saturation level, to roughly estimate an individual article's current stage in the life cycle and its potential to attract future attention. The proposed approach can also be extended to higher levels of aggregation (e.g., individual scientists, journals, institutions), providing further insights into the practice of scientific evaluation.
Inhalt: Vgl.: https://onlinelibrary.wiley.com/doi/10.1002/asi.24047.
3Li, J. ; Sun, A. ; Xing, Z.: To do or not to do : distill crowdsourced negative caveats to augment api documentation.
In: Journal of the Association for Information Science and Technology. 69(2018) no.12, S.1460-1475.
Abstract: Negative caveats of application programming interfaces (APIs) are about "how not to use an API," which are often absent from the official API documentation. When these caveats are overlooked, programming errors may emerge from misusing APIs, leading to heavy discussions on Q&A websites like Stack Overflow. If the overlooked caveats could be mined from these discussions, they would be beneficial for programmers to avoid misuse of APIs. However, it is challenging because the discussions are informal, redundant, and diverse. For this, for example, we propose Disca, a novel approach for automatically Distilling desirable API negative caveats from unstructured Q&A discussions. Through sentence selection and prominent term clustering, Disca ensures that distilled caveats are context-independent, prominent, semantically diverse, and nonredundant. Quantitative evaluation in our experiments shows that the proposed Disca significantly outperforms four text-summarization techniques. We also show that the distilled API negative caveats could greatly augment API documentation through qualitative analysis.
4Shi, D. ; Rousseau, R. ; Yang, L. ; Li, J.: ¬A journal's impact factor is influenced by changes in publication delays of citing journals.
In: Journal of the Association for Information Science and Technology. 68(2017) no.3, S.780-789.
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.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23706/full.
5Li, J. ; Zhang, P. ; Song, D. ; Wu, Y.: Understanding an enriched multidimensional user relevance model by analyzing query logs.
In: Journal of the Association for Information Science and Technology. 68(2017) no.12, S.2743-2754.
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.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23868/full.
6Li, J. ; Shi, D.: Sleeping beauties in genius work : when were they awakened?.
In: Journal of the Association for Information Science and Technology. 67(2016) no.2, S.432-440.
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.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23380/abstract.
7Zhu, Q. ; Kong, X. ; Hong, S. ; Li, J. ; He, Z.: Global ontology research progress : a bibliometric analysis.
In: Aslib journal of information management. 67(2015) no.1, S.27-54.
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.
Inhalt: Vgl.: http://dx.doi.org/10.1108/AJIM-09-2014-0112.
8Zhao, S.X. ; Zhang, P.L. ; Li, J. ; Tan, A.M. ; Ye, F.Y.: Abstracting the core subnet of weighted networks based on link strengths.
In: Journal of the Association for Information Science and Technology. 65(2014) no.5, S.984-994.
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.
9Wu, S. ; Li, J. ; Zeng, X. ; Bi, Y.: Adaptive data fusion methods in information retrieval.
In: Journal of the Association for Information Science and Technology. 65(2014) no.10, S.2048-2061.
Abstract: Data fusion is currently used extensively in information retrieval for various tasks. It has proved to be a useful technology because it is able to improve retrieval performance frequently. However, in almost all prior research in data fusion, static search environments have been used, and dynamic search environments have generally not been considered. In this article, we investigate adaptive data fusion methods that can change their behavior when the search environment changes. Three adaptive data fusion methods are proposed and investigated. To test these proposed methods properly, we generate a benchmark from a historic Text REtrieval Conference data set. Experiments with the benchmark show that 2 of the proposed methods are good and may potentially be used in practice.
10Lin, N. ; Li, D. ; Ding, Y. ; He, B. ; Qin, Z. ; Tang, J. ; Li, J. ; Dong, T.: ¬The dynamic features of Delicious, Flickr, and YouTube.
In: Journal of the American Society for Information Science and Technology. 63(2012) no.1, S.139-162.
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.
Themenfeld: Social tagging
Objekt: Delicious ; Flickr ; YouTube
11Li, J. ; Willett, P.: ArticleRank : a PageRank-based alternative to numbers of citations for analysing citation networks.
In: Aslib proceedings. 61(2009) no.6, S.605-618.
Abstract: Purpose - The purpose of this paper is to suggest an alternative to the widely used Times Cited criterion for analysing citation networks. The approach involves taking account of the natures of the papers that cite a given paper, so as to differentiate between papers that attract the same number of citations. Design/methodology/approach - ArticleRank is an algorithm that has been derived from Google's PageRank algorithm to measure the influence of journal articles. ArticleRank is applied to two datasets - a citation network based on an early paper on webometrics, and a self-citation network based on the 19 most cited papers in the Journal of Documentation - using citation data taken from the Web of Knowledge database. Findings - ArticleRank values provide a different ranking of a set of papers from that provided by the corresponding Times Cited values, and overcomes the inability of the latter to differentiate between papers with the same numbers of citations. The difference in rankings between Times Cited and ArticleRank is greatest for the most heavily cited articles in a dataset. Originality/value - This is a novel application of the PageRank algorithm.
Themenfeld: Retrievalalgorithmen ; Informetrie
Objekt: ArticleRank ; PageRank
12Li, J. ; Zhang, P. ; Cao, J.: External concept support for group support systems through Web mining.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.5, S.1057-1070.
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.
Themenfeld: Data Mining
13Zhang, C. ; Zeng, D. ; Li, J. ; Wang, F.-Y. ; Zuo, W.: Sentiment analysis of Chinese documents : from sentence to document level.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2474-2487.
Abstract: User-generated content on the Web has become an extremely valuable source for mining and analyzing user opinions on any topic. Recent years have seen an increasing body of work investigating methods to recognize favorable and unfavorable sentiments toward specific subjects from online text. However, most of these efforts focus on English and there have been very few studies on sentiment analysis of Chinese content. This paper aims to address the unique challenges posed by Chinese sentiment analysis. We propose a rule-based approach including two phases: (1) determining each sentence's sentiment based on word dependency, and (2) aggregating sentences to predict the document sentiment. We report the results of an experimental study comparing our approach with three machine learning-based approaches using two sets of Chinese articles. These results illustrate the effectiveness of our proposed method and its advantages against learning-based approaches.
14Li, J. ; Zhang, Z. ; Li, X. ; Chen, H.: Kernel-based learning for biomedical relation extraction.
In: Journal of the American Society for Information Science and Technology. 59(2008) no.5, S.756-769.
Abstract: Relation extraction is the process of scanning text for relationships between named entities. Recently, significant studies have focused on automatically extracting relations from biomedical corpora. Most existing biomedical relation extractors require manual creation of biomedical lexicons or parsing templates based on domain knowledge. In this study, we propose to use kernel-based learning methods to automatically extract biomedical relations from literature text. We develop a framework of kernel-based learning for biomedical relation extraction. In particular, we modified the standard tree kernel function by incorporating a trace kernel to capture richer contextual information. In our experiments on a biomedical corpus, we compare different kernel functions for biomedical relation detection and classification. The experimental results show that a tree kernel outperforms word and sequence kernels for relation detection, our trace-tree kernel outperforms the standard tree kernel, and a composite kernel outperforms individual kernels for relation extraction.
15Lin, X. ; Li, J. ; Zhou, X.: Theme creation for digital collections.
In: 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. Göttingen : Univ.-Verl., 2008. S.34-42.
Abstract: This paper presents an approach for integrating multiple sources of semantics for the creating metadata. A new framework is proposed to define topics and themes with both manually and automatically generated terms. The automatically generated terms include: terms from a semantic analysis of the collections and terms from previous user's queries. An interface is developed to facilitate the creation and use of such topics and themes for metadata creation. The framework and the interface promote human-computer collaboration in metadata creation. Several principles underlying such approach are also discussed.
Inhalt: Vgl. unter: http://dcpapers.dublincore.org/ojs/pubs/article/view/917/913.
Objekt: Topic maps
16Zheng, R. ; Li, J. ; Chen, H. ; Huang, Z.: ¬A framework for authorship identification of online messages : writing-style features and classification techniques.
In: Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.378-393.
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.
17Tang, J. ; Liang, B.-Y. ; Li, J.-Z.: Toward detecting mapping strategies for ontology interoperability.
Abstract: Ontology mapping is one of the core tasks for ontology interoperability. It is aimed to find semantic relationships between entities (i.e. concept, attribute, and relation) of two ontologies. It benefits many applications, such as integration of ontology based web data sources, interoperability of agents or web services. To reduce the amount of users' effort as much as possible, (semi-) automatic ontology mapping is becoming more and more important to bring it into fruition. In the existing literature, many approaches have found considerable interest by combining several different similar/mapping strategies (namely multi-strategy based mapping). However, experiments show that the multi-strategy based mapping does not always outperform its single-strategy counterpart. In this paper, we mainly aim to deal with two problems: (1) for a new, unseen mapping task, should we select a multi-strategy based algorithm or just one single-strategy based algorithm? (2) if the task is suitable for multi-strategy, then how to select the strategies into the final combined scenario? We propose an approach of multiple strategies detections for ontology mapping. The results obtained so far show that multi-strategy detection improves on precision and recall significantly.
Inhalt: Beitrag anlässlich: Workshop on The Semantic Computing Initiative (SeC 2005) --- From Semantic Web to Semantic World --- to be held in conjunction with The 14th Int'l Conf. on World Wide Web (WWW2005); vgl.: http://www.instsec.org/2005ws/.
Themenfeld: Semantische Interoperabilität
19Li, J. ; Wu, G.: Characteristics of reference transactions : challenges to librarian's roles.
In: Bulletin of the Medical Library Association. 86(1998) no.4, S.610-612.
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
Anmerkung: Article included in a special section devoted to work undertaken as part of the University of Iowa Digital Library Project
20Paoli, J.: Extending the Web's tag set using SGML : authoring new tags with Grif Symposia.
In: Computer networks and ISDN systems. 28(1996) nos.7/11, S.1095-1104.
Abstract: Discusses the advantages of using a mixed HTML/SGML data model for the WWW. The Grif Symposia has developed an integrated authoring browsing environment with full extensible capabilities to handle mixed HTML/SGML data models. Presents the different layers developed for the Grif Symposia and highlights the advantages of authoring in a mixed SGML/HTML environment
Objekt: WWW ; HTML ; SGML