Search (6 results, page 1 of 1)

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Abstract

Each section header of an article has its distinct communicative function. Citations from distinct sections may be different regarding citing motivation. In this paper, we grouped section headers with similar functions as a structural function and defined the distribution of citations from structural functions for a paper as its citation structure. We aim to explore the relationship between citation structure and the future impact of a publication and disclose the relative importance among citations from different structural functions. Specifically, we proposed two citation counting methods and a citation life cycle identification method, by which the regression data were built. Subsequently, we employed a ridge regression model to predict the future impact of the paper and analyzed the relative weights of regressors. Based on documents collected from the Association for Computational Linguistics Anthology website, our empirical experiments disclosed that functional structure features improve the prediction accuracy of citation count prediction and that there exist differences among citations from different structural functions. Specifically, at the early stage of citation lifetime, citations from Introduction and Method are particularly important for perceiving future impact of papers, and citations from Result and Conclusion are also vital. However, early accumulation of citations from the Background seems less important.

Theme

Citation indexing

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Abstract

This article investigates the lengths of time that publications with different numbers of citations take to receive their first citation (the beginning stage), and then compares the lengths of time to receive two or more citations after receiving the first citation (the accumulative stage) in the field of computer science. We find that in the beginning stage, that is, from zero to one citation, high-, medium-, and low-cited publications do not obviously exhibit different lengths of time. However, in the accumulative stage, that is, from one to N citations, highly cited publications begin to receive citations much more rapidly than medium- and low-cited publications. Moreover, as N increases, the difference in receiving new citations among high-, medium-, and low-cited publications increases quite significantly.

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Abstract

Purpose - Being an important data exchange and information storage standard, XML has generated a great deal of interest and particular attention has been paid to the issue of XML indexing. Clear use cases for structured search in XML have been established. However, most of the research in the area is either based on relational database systems or specialized semi-structured data management systems. This paper aims to propose a method for XML indexing based on the information retrieval (IR) system Okapi. Design/methodology/approach - First, the paper reviews the structure of inverted files and gives an overview of the issues of why this indexing mechanism cannot properly support XML retrieval, using the underlying data structures of Okapi as an example. Then the paper explores a revised method implemented on Okapi using path indexing structures. The paper evaluates these index structures through the metrics of indexing run time, path search run time and space costs using the INEX and Reuters RVC1 collections. Findings - Initial results on the INEX collections show that there is a substantial overhead in space costs for the method, but this increase does not affect run time adversely. Indexing results on differing sized Reuters RVC1 sub-collections show that the increase in space costs with increasing the size of a collection is significant, but in terms of run time the increase is linear. Path search results show sub-millisecond run times, demonstrating minimal overhead for XML search. Practical implications - Overall, the results show the method implemented to support XML search in a traditional IR system such as Okapi is viable. Originality/value - The paper provides useful information on a method for XML indexing based on the IR system Okapi.

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Date

20. 1.2015 18:30:22

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Date

22. 1.2023 18:40:36

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Date

22. 6.2023 14:55:20