Citation Proximity Analysis (CPA) – A new approach for identifying related work based on Co-Citation Analysis

Bela Gipp1 and Jöran Beel2
Bela@Gipp.com, 2 Joeran@Beel.org Otto-von-Guericke University, Dept. of Computer Science, Magdeburg, Germany
1

Abstract
This paper presents an approach for identifying similar documents that can be used to assist scientists in finding related work. The approach called Citation Proximity Analysis (CPA) is a further development of co-citation analysis, but in addition, considers the proximity of citations to each other within an article‟s full-text. The underlying idea is that the closer citations are to each other, the more likely it is that they are related. In comparison to existing approaches, such as bibliographic coupling, co-citation analysis or keyword based approaches the advantages of CPA are a higher precision and the possibility to identify related sections within documents. Moreover, CPA allows a more precise automatic document classification. CPA is used as the primary approach to analyse the similarity and to classify the 1.2 million publications contained in the research paper recommender system Scienstein.org.

Introduction and Motivation The search for related scientific work can be tedious, and often important documents are missed out. Difficulties are caused by an increasing number of publications, growing exponentially at a yearly rate of 3.7 %, unclear nomenclature, synonyms and numerous other factors [1]. In practice, most searches for related work start with some initial papers and navigating the citation web nearest to those papers. However, even the more advanced approaches for identifying related work based on co-word analysis, collaborative filtering, Subject-Action-Object (SAO) structures or citation analysis do often not deliver satisfying results [2-8]. Therefore, we developed a new approach to determine the similarity of documents, which we name Citation Proximity Analysis (CPA). The approach is based on cocitation analysis and improves precision by considering the position of citations. The presented approach was developed for the research paper recommender Scienstein1 to assist researchers in finding related work. The first part of this paper gives an overview about existing methods to identify similar documents, whereas the focus lies on the most popular citation analysis approaches and their strengths and weaknesses. The second part explains how the CPA can be used to measure similarity and the steps necessary to calculate a new metric that we call Citation Proximity Index (CPI). Afterwards, first results from an empirical study comparing the performance of co-citation analysis and CPA are presented. Finally, an outlook on further implications and how the CPA could be used in other fields is given.

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www.scienstein.org is a research paper recommender focusing on identifying related work developed by the authors

which considers papers as relevant that cite the same input document and the „reference list‟ approach.ist. co-citation is essentially a forward-looking perspective [9]. Figure 2: Co-citation analysis Although both approaches are suitable to identify similar papers. Figure 1 illustrates this approach: Papers A and B are related because they both cite papers C. both approaches often deliver unsatisfying results.Related Work Various approaches exist to determine the degree of similarity of documents in order to identify related work.edu The citations were parsed using a modified version of parsCit (http://wing. are used by scientists and on academic search engine websites like CiteSeer2 [9]. However. The document is parsed and a series of heuristics are used to process the citations including their position within the document3. Since these approaches are system-inherent. which considers papers as relevant that were referenced by the input document.psu. .sg/parsCit) in combination with exclusively developed software. Whereas text-mining approaches are used in cases in which references are not stated. These approaches. D and E. 2 3 http://citeseer. Doc C cites Doc D Doc E Doc A cited Doc B cited cites In contrast. The best results can usually be obtained by bibliographic coupling and co-citation analysis. two documents are “cocited” when at least one paper cites both. citation analysis approaches usually deliver superior results as e. Doc A citing Doc C cites Doc D Doc E cites Doc B citing Documents are bibliographically coupled if they cite one or more documents in common.edu. 1. This approach is illustrated in Figure 2: Papers A and B are related because they Figure 1: Bibliographic coupling are both cited by papers C. they serve different purposes. D and E.nus.comp. synonyms and unclear nomenclature do not lead to misleading results [3. The more co-citations two papers receive. since they only make use of the bibliography at the end of the document without analysing the constellation of citations. that allow calculating the coupling strength [6]. Citation Proximity Analysis (CPA) Instead of just using the bibliography. Among the most widely used are the easily applicable „cited by‟ approach. in CPA the information derived from the proximity of the citations to each other in the full-text is used to calculate the Citation Proximity Index (CPI) in three steps. which is available upon request from the authors. it is also not possible to determine in which part of a related document the content of interest can be found. the more related they are [6]. Whereas bibliographic coupling is retrospective. 4. Many citation analysis approaches exist and they all have their own strengths and weaknesses for identifying similar documents. 5].g. which were already invented in the 60s and 70s.

Another example. This is an example text with references to different documents. Another example. The 21 study participants have been asked to select three similar documents from the Scienstein. This is another reference. Another exampleThis is an example text with references to different documents. This is an example text with references to different documents. This is an example text with references to different documents. This is an example text with references to different documents. This is an example text with references to different documents. If for example two citations are given in the same sentence the probability that they are very similar is higher (CPI = 1) as if they were only in the same paragraph (CPI = ¼). This is an example text with references to different documents. further research needs to be Figure 3: Illustration of Citation Proximity Analysis performed to identify the appropriate weighting of the CPI values according to their occurrence. Another example. The overall margin of error with the system we have developed equals nearly three percent for the first and second step. Another example.Another example.Another example. This is an example text with references to different documents.This is an example text with references to different documents. This is an example text with references to different documents. This is an example text with references to different documents. This is an example text with references to different documents. Another example. [2]. Another example. This is an example text with references to different documents. Another example [3]. Another example.This is an example text with references to different documents.Another example.[1] Another example. Two very similar references [1]. Another example. This is an example text with references to different documents. Another example. Another example. This is an example text with references to different documents [1]. 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This is an example text with references to different documents. Another example. The underlying assumption is that the closer the citations are to each other the more likely it is that they are related. Another example. Another example. This is an example text with references to different documents. Example. Another example. The complete study will be published separately. This is an example text with references to different documents.Another example. This can be the case due to multiple occurrences of the same citation and due to multiple documents citing a certain document. 3.Another example. The citations are assigned to their corresponding items in the bibliography. This is an example text with references to different documents. Another example. This is an example text with references to different documents [1]. See Figure 3. Another example. Another example. Example. Another example. This is an example text with references to different documents. This is one reference [1]. This is an example text with references to different documents.This is an example text with references to different documents. This is an example text with references to different documents. In our series of tests we experienced the best results by calculating the weighted average of the CPIs. This is an example text with references to different documents. Another exampleThis is an example text with references to different documents. The results show that the CPA performs significantly better in identifying related work than the commonly-used Co-citation analysis. first results of a study examining the suitability of CPA to identify related work are presented. Document 1 This is an example text with references to different documents. This is one reference [1]. This is an example text with references to different documents. which also seems to depend on the publication‟s research field and publication‟s research type. Another example. Another example. we have calculated the CPI for publications contained in the Scienstein database.Another example. Occurrence Sentence Paragraph Chapter Same journal / same book Same journal but different edition CPI value 1 1/2 1/4 1/8 Empirical Comparison of Co-Citation Analysis and CPA In the following. CPA delivers considerably better results in identifying similar documents.Another example. Another example. This is an example text with references to different documents.org database and then six “related work recommendations” have been provided. Another example.Another example. Another example. This is another reference [2]. Another example. different weightings seem suitable. Document 3 Another example. This is an example text with references to different documents. This is an example text with references to different documents.This is an example text with references to different documents. This is an example text with references to different documents. This is another reference [2]. Example. This is an example text with references to different documents. Another example. [2]. First empirical evaluations have lead to the values shown in Table 1 for calculating the CPI.Another example. Another example.Another example. This is an example text with references to different documents. Another example. This is an example text with references to different documents. Another example. Another example. This is an example text with references to different documents. This is an example text with references to different documents. In the third step the proximity among each citation-pair is examined. Based on this proximity analysis. Another example [3]. This is an example text with references to different documents. This is an example text with references to different documents. Example. This is an example text with references to different documents. This is an example text with references to different documents. This is an example text with references to different documents. This is an example text with references to different documents. This is an example text with references to different documents.This is an example text with references to different documents. the focus laid on a comparison with Co-citation analysis as this approach usually delivers the best results. Another example. This is one reference [1]. This is an example text with references to different documents.Another example. Another example.Another example. Another example. This is an example text with references to different documents. This is an example text with references to different documents. Table 1: CPI Values The results delivered by CPA can be improved by evaluating as many sources as possible. Document 2 This is an example text with references to different documents.2. This is an example text with references to different documents. This is an example text with references to different documents. 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„Length contraction‟ or „Massenergy equivalence‟ and then to give specific recommendations within documents or books. the authors currently apply the idea behind CPA for automatic document classification for the research paper recommender Scienstein [11]. Not surprisingly. the study also substantiated the assumption that especially for documents with extensive bibliography or documents that have not been referenced frequently.library. on „Time dilation’. It is also often possible by knowing the position of each citation within a document to draw conclusions about the document type e. which is in practice not always possible. So instead of knowing.g. it is not surprising that CPA outperforms Cocitation analysis in every examined scenario4. and leads in ca. it is possible to combine the CPA with text mining algorithms in order to automatically detect e. We believe that these technologies in combination with collaborative filtering will be the future for identifying related work and will open the doors for powerful research paper recommender systems. Outlook & Conclusion Besides identifying related work. state-of-the art publications etc. The aim is to automatically analyse the topics within documents by analysing the distribution of references within research papers. identify each reference and map it to the corresponding entry in the bibliography. CPA delivers superior results...garfield. nearly twice as many study participants obtained more suitable documents when the CPA was used in comparison to the documents obtained by co-citation analysis. it should also be taken into account that the effort to calculate the CPA is considerable. Taking into consideration that CPA essentially works like co-citation analysis with the distinctive difference that the proximity among citations is analysed and therefore additional information about relatedness is gathered. 3% of cases to mismatches. “The author A has shown in his recent study [reference A] that in contrast to a previous study [reference B].” So by analysing the words between two references it is often possible to automatically analyse in which relationship these two references stand to each other. contradicting studies. It is not sufficient to evaluate the bibliography of documents.edu/papers/mapsciworld. The gained information can be used to classify further documents and to develop a more sophisticated „Web of Science‟5.html . for instance. As shown. However.Figure 4: Comparison of CPA and Co-citation analysis As the pie chart indicates. the CPA makes it possible to identify the document sections focusing for example. Moreover.upenn.g. This is because sometimes only an 4 5 A detailed description of the study and its results will be published seperatly. the CPA offers substantial advantages in identifying related documents in comparison to existing approaches. http://www. that a certain publication focuses on the relativity theory. but it is necessary to process the complete document.

New York: Reinhold Publ. Nauchno-Tekhnicheskaya Informatsiya. Masoodian & S. K. 381-400. Griffith. (Edts). C. C. [2] Rip. 275. Buchanan. 1998.abstract and the bibliography can be accessed.1007/978-3540-89533-6. documents cannot be parsed as OCR6 fails. (2006). I. Co-citation in the scientific literature: a new measure of the relationship between two documents. 3–8. pp. pp. Digital Libraries: Universal and Ubiquitous Access to Information of Lecture Notes in Computer Science. pp. B.5. Perry. No.. 89-98. Tamil Nadu. I. [6] Small. DOI 10. No. Kuta. M. no. H. W. [4] Marshakova. & Gipp. [10] Giles. H.). Paper presented at the Drexel University. D. Journal of the American Society for Information Science and Technology. Science. And Lawrence. 238 –244. A. the 11th International Conference on Digital Asian Libraries (ICADL 2008). The Potential of Collaborative Document Evaluation for Science. In Digital Libraries 98 . 1956. it cannot completely replace co-citation analysis. Identifying a better measure of relatedness for mapping science. 113-130. (2001. M. J. Vol. R. References [1] May. C. This leads to the conclusion that although the CPA delivers superior results. Springer-Verlag Berlin Heidelberg. J. L. From Bibliographic Coupling to Co-CitationAnalysis Via Algorithmic Historio-Bibliography: A Citationist‟s Tribute to BelverC. November 27. Bergmann. S. Vol. B.. (2009). pp. 1. & Hentschel. & Boyack. Kent. Bollacker. Beel. 57. [9] Garfield. J. [7] Klavans. vol. pp. in Documentation in Action.The Third ACM Conference on Digital Libraries. 2. [8] Sternitzke. 6(6). K. pp. M. A. 2. PA. 2001). Co-Word Maps of Biotechnology: An Example of Cognitive Scientometrics. Journal of the American Society for Information Science. vol. ISSN 0302-9743. 5301. (2009). [5] Beel. 2008. 251-263. Scientometrics. 78. vol. R. Shera. 5362. India. E. [3] Fano. The Scientific Wealth of Nations. 793-796. 265 –269. J.. & Courtial. CiteSeer: an automatic citation indexing system. Philadelphia. Indonesia. pp. Cunningham (Eds. J. [11] Gipp. Scienstein . or a reference style is used that makes it unfeasible to automatically link references to the corresponding items in the bibliography. R. V. (1984). Scientometrics. vol. 24. pp. Co. 1997. 1973. 1973. published in G. 6. in Proceedings of IEEE International Conference on Emerging Trends in Computing. no. 375-378. 6 Optical Character Recognition . System of document connections based on references.A Research Paper Recommender System. December 2 . Similarity measures for document mapping: A comparative study on the level of an individual scientist. Information theory and the retrieval of recorded information.

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