calculated. If for example two citations are given in the the weighted average of the CPls. By automating the same sentence the probability that they are very similar is process described above, we have calculated the CPI for higher(CPI= 1) as if they were only in the same paragraph publications contained in the SciPlore database. The results (CPI= 1/2). See Figure 5 show that in comparison to the results delivered by co- citation analysis, CPa delivers considerably better results in Citing Document identifying similar documents [1] Similar to the idea of CPa is another approach currently under development, that we call Citation Order Analysi (COA). In contrast to CPA, in COA, only the order of citations is considered. The main advantage in comparison to the usually applied text analysis approaches is that even if documents are translated or paraphrased they can still be identified as similar. Depending on the level of tolerance even if citations were omitted. summarized documents can Document 1 be identified. This way a digital fingerprint of documents can be created that can, besides for recommender systems 回三 also be used to identify plagiarized work. In some regard this approach is similar to bibliographic coupling. However, by additionally considering the order of citations, this approach is more precise and robust. Figure 6 illustrates the concept. Document A Document B Figure 5: Illustration CPA However, further research needs to be performed to identify the appropriate weighting of the CPI values according to their occurrence, which also seems to depend on the publications research field and publications research type For example, it seems that for analyzing a technical report or patent specification, different weightings seem suitable First empirical evaluations have lead to the values shown in Figure 6: Illustration Citation Order Analysis Table I for calculating the CPl IV OUTLOOK Besides identifying related work, the authors work on Table 1: cpi values applying the idea behind CPA for automatic document CPI value classification for the research paper recommender SciPlore 1]. The aim is to automatically analyze the topics within documents by analyzing the distribution of references within research papers. So instead of knowing, for instance, Chapter that a certain publication focuses on the relativity theor Same journal same book the CPa makes it possible to identify the document sections Same journal but different edition l/16 focusing example,on‘ Time dilation;‘ Length contraction'or'Mass-energy equivalence' and then to give specific recommendations within documents or books The results delivered by CPA can be improved by Moreover, it is possible to combine the CPA with text evaluating as many sources as possible. This can be the mining algorithms in order to automatically detect e. g case due to multiple occurrences of the same citation and contradicting studies. "The author A has shown in his due to multiple documents citing a certain document. In our recent study /reference A that in contrast to a previousrelated. Based on this proximity analysis, the CPI is calculated. 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 = 1/2). See Figure 5. This is an example text with references to different documents. 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. 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. Another example [3]. 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]. Another exampleThis is an example text with references to different documents. Another example. 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This is an example text with references to different documents. Two very similar references [1],[2]. This is an example text with references to different documents.This is an example text with references to different documents.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. This is an example text with references to different documents. 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. 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. Another example. 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For example, it seems that for analyzing a technical report or patent specification, different weightings seem suitable. First empirical evaluations have lead to the values shown in Table 1 for calculating the CPI. Table 1: CPI values The results delivered by CPA can be improved by evaluating as many sources as possible. This can be the case due to multiple occurrences of the same citation and due to multiple documents citing a certain document. In our series of tests we experienced the best results by calculating the weighted average of the CPIs. By automating the process described above, we have calculated the CPI for publications contained in the SciPlore database. The results show that in comparison to the results delivered by co￾citation analysis, CPA delivers considerably better results in identifying similar documents [1]. Similar to the idea of CPA is another approach currently under development, that we call Citation Order Analysis (COA). In contrast to CPA, in COA, only the order of citations is considered. The main advantage in comparison to the usually applied text analysis approaches is that even if documents are translated or paraphrased they can still be identified as similar. Depending on the level of tolerance even if citations were omitted, summarized documents can be identified. This way a digital fingerprint of documents can be created that can, besides for recommender systems, also be used to identify plagiarized work. In some regard, this approach is similar to bibliographic coupling. However, by additionally considering the order of citations, this approach is more precise and robust. Figure 6 illustrates the concept. This is an example text with references to different documents.[1] Another example. This is an example text with references to different documents.This is an example text with references to different documents. This is one reference [1], [2]. 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This is an example text with references to different documents. Document A This is an example text with references to different documents.[1] Another example. This is an example This is an example text with references to different documents.[1] Another example. This is an example text with references to different documents.This is an ex This is an example text with references to different documents.This is an ex asdasdasd Document B Figure 6: Illustration Citation Order Analysis IV. OUTLOOK Besides identifying related work, the authors work on applying the idea behind CPA for automatic document classification for the research paper recommender SciPlore [11]. The aim is to automatically analyze the topics within documents by analyzing the distribution of references within research papers. So instead of knowing, for instance, that a certain publication focuses on the relativity theory, the CPA makes it possible to identify the document sections focusing for example, on „Time dilation’, „Length contraction‟ or „Mass-energy equivalence‟ and then to give specific recommendations within documents or books. Moreover, it is possible to combine the CPA with text mining algorithms in order to automatically detect e.g. contradicting studies. “The author A has shown in his recent study [reference A] that in contrast to a previous Occurrence CPI value Sentence 1 Paragraph 1/2 Chapter 1/4 Same journal / same book 1/8 Same journal but different edition 1/16