**1. Introduction**

Citation analysis is a bibliometric analysis technique which reveals the quantitative characteristics and laws of scholarly publications. It involves the use of mathematical and statistical methods to analyze citations within journals, papers, authors, and other references. Citation analysis has seen substantial theoretical and practical progress over several decades of development and has been widely applied to evaluate scientific knowledge, identify scientific models, and explore new frontiers which being explored by the scientific community. It is of great significance in regard to technological innovation and scientific decision-making. Traditional

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

citation analysis methods and tools are overly dependent on citation databases, which have the following drawbacks:

citation types include factual relationships and rhetorical relationships. The current version (CiTO 2.4.6) allows authors to describe their citation motivations as references, thus helping to reveal indirect and implicit relationships at work in scholarly literature. Ciancarini et al. [7] presented an experiment to investigate which are the main difficulties behind CiTO and how the humans understand and adopt CiTO. Iorio et al. [8] proposed a tool called CiTalO, which could automatically annotate the nature of citations with properties defined in CiTO through the semantic web and NLP techniques. By contrast, Recupero et al. [9] created SHELDON to extract citation RDF data from text using a machine reader, and CiTO was also used to

The Impact on Citation Analysis Based on Ontology and Linked Data

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Other researchers, for example, Ding, Konidena, Sun, and Chen [10], have also explored the idea of semantic citation to suggest that individuals can use ontology and linked data to describe bibliographic data and publish it to RDF triples. Mahmood, Qadir, and Afzal [11] combined semantic web technology with credible citation analysis to establish a framework that provides openness and reliability validation for all stages of the citation behavior lifecycle. The framework requires the use of semantic metadata at all stages of academic publishing to annotate the citation behavior and generate machine-readable RDF triples. This kind of annotation makes author, publisher, database vendor, and citation analysis system work together and build a set of reliable reference information while eliminating any false or misleading citation actions in the literature. More recently, Peroni et al. [12] experimentally described references in a suitable machine-readable RDF formats to make reference lists freely available to all academics. The

open citation corpus [13] is created to store citation data from open access databases.

Quickly moving into an unfamiliar field for researchers is difficult, due to the mass of scientific articles [14] that must be reviewed without prior knowledge of their research contents. In a traditional citation information service, the search results are generated by keywords and other information that match specific knowledge resources and the corresponding user's correspondence. Such a method is simple, but it often ignores the semantic level of the knowledge resources, causing it to miss a significant number of semantic knowledge resources [15]. It may yield search results from a large number of studies that still do not meet the user's

In 2001, Aronson [17] argued that query refinement based on ontology is more efficient than other methods that were available at the time. From the perspective of information organization, ontology is a new method of knowledge organization and processing, and it is also the basis of semantic webs. It can systematize and organize a large amount of relevant information. When applying ontology to information retrieval, it is necessary to apply ontological principles to the information resources, so that search reasoning is implemented by the logical rules contained in the ontology itself, and a high quality retrieval result is output. With respect to the shortcomings of traditional citation information services, the introduction of ontology may help users to improve their searches aimed at multiple citation retrieval. In 2012, Kara, Alan, Sabuncu, Akpınar, Cicekli, and Alpaslan [18] found that while thesauruses are concerned with meanings at the level of words, ontologies more specifically deal with meanings at the level of real-world entities denoted by words. That is, ontologies deal with

describe the citation relationship.

personalized knowledge needs [16].

the interpretation of words in terms of real-world entities.


Motivations and behaviors related to citation have been analyzed by researchers from various angles. In 2014, content-based citation analysis method [1] has also been proposed. In this chapter, we propose a new citation analysis framework based on ontology and linked data; our goal is to enhance the efficacy of citation analysis via semantic web technology.
