Co-citation Proximity Analysis

	Co-citation Proximity Analysis Co-citation Proximity Analysis or CPA is a document similarity measure that uses citation analysis to assess semantic similarity between documents at both the global document level as well as at individual section-level.Bela Gipp and Joeran Beel, 200"Citation Proximity Analysis (CPA) – A new approach for identifying related work based on Co-Citation Analysis"in Birger Larsen and Jacqueline Leta, editors, Proceedings of the 12th International Conference on Scientometrics and Informetrics (ISSI’09), volume 2, pages 571–575, Rio de Janeiro (Brazil), July 2009. The similarity measure builds on the Co-citation, co-citation analysis approach, but differs in that it exploits the information implied in the placement of citations within the full-texts of documents. Co-citation Proximity Analysis was conceived by B. Gipp in 2006 and the description of the document similarity measure was later published by Gipp and Beel in 2009. The similarity measure rests on the assumption that withi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Co-citation Proximity Analysis Concept Co-citation is the frequency with which two documents are ''cited'' together by other documents.. If at least one other document cites two documents in common, these documents are said to be ''co-cited''. The more co-citations two documents receive, the higher their co-citation strength, and the more likely they are semantically related. Like bibliographic coupling, co-citation is a semantic similarity measure for documents that makes use of citation analyses. The figure to the right illustrates the concept of co-citation and a more recent variation of co-citation which accounts for the placement of citations in the full text of documents. The figure's left image shows the Documents A and B, which are both cited by Documents C, D and E; thus Documents A and B have a co-citation strength, or co-citation indexJeppe Nicolaisen, 200Co-citation, in Birger Hjørland, ed. from The Royal School of Library and Information Science (RSLIS), Copenhagen, Denmark. of three. This score is usual ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Similarity Measure In statistics and related fields, a similarity measure or similarity function or similarity metric is a real-valued function that quantifies the similarity between two objects. Although no single definition of a similarity exists, usually such measures are in some sense the inverse of distance metrics: they take on large values for similar objects and either zero or a negative value for very dissimilar objects. Though, in more broad terms, a similarity function may also satisfy metric axioms. Cosine similarity is a commonly used similarity measure for real-valued vectors, used in (among other fields) information retrieval to score the similarity of documents in the vector space model. In machine learning, common kernel functions such as the RBF kernel can be viewed as similarity functions. Use in clustering In spectral clustering, a similarity, or affinity, measure is used to transform data to overcome difficulties related to lack of convexity in the shape of the data distribut ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Citation Analysis Citation analysis is the examination of the frequency, patterns, and graphs of citations in documents. It uses the directed graph of citations — links from one document to another document — to reveal properties of the documents. A typical aim would be to identify the most important documents in a collection. A classic example is that of the citations between academic articles and books. For another example, judges of law support their judgements by referring back to judgements made in earlier cases (see citation analysis in a legal context). An additional example is provided by patents which contain prior art, citation of earlier patents relevant to the current claim. Documents can be associated with many other features in addition to citations, such as authors, publishers, journals as well as their actual texts. The general analysis of collections of documents is known as bibliometrics and citation analysis is a key part of that field. For example, bibliographic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Semantic Similarity Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of language, concepts or instances, through a numerical description obtained according to the comparison of information supporting their meaning or describing their nature. The term semantic similarity is often confused with semantic relatedness. Semantic relatedness includes any relation between two terms, while semantic similarity only includes "is a" relations. For example, "car" is similar to "bus", but is also related to "road" and "driving". Computationally, semantic similarity can be estimated by defining a topological similarity, by using ontologies to define the distance between terms/concepts. For example, a naive metric for the comparison of concepts order ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Co-citation Co-citation is the frequency with which two documents are ''cited'' together by other documents.. If at least one other document cites two documents in common, these documents are said to be ''co-cited''. The more co-citations two documents receive, the higher their co-citation strength, and the more likely they are semantically related. Like bibliographic coupling, co-citation is a semantic similarity measure for documents that makes use of citation analyses. The figure to the right illustrates the concept of co-citation and a more recent variation of co-citation which accounts for the placement of citations in the full text of documents. The figure's left image shows the Documents A and B, which are both cited by Documents C, D and E; thus Documents A and B have a co-citation strength, or co-citation indexJeppe Nicolaisen, 200Co-citation, in Birger Hjørland, ed. from The Royal School of Library and Information Science (RSLIS), Copenhagen, Denmark. of three. This score is usua ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Bibliographic Coupling Bibliographic coupling, like co-citation, is a similarity measure that uses citation analysis to establish a similarity relationship between documents. Bibliographic coupling occurs when two works reference a common third work in their bibliographies. It is an indication that a probability exists that the two works treat a related subject matter. Two documents are ''bibliographically coupled'' if they both ''cite'' one or more documents in common. The "coupling strength" of two given documents is higher the more citations to other documents they share. The figure to the right illustrates the concept of bibliographic coupling. In the figure, documents A and B both cite documents C, D and E. Thus, documents A and B have a bibliographic coupling strength of 3 - the number of elements in the intersection of their two reference lists. Similarly, two authors are ''bibliographically coupled'' if the cumulative reference lists of their respective oeuvres each contain a reference to a commo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Volker Markl Volker Markl (born 1971) is a German computer scientist and database systems researcher. Career In 1999, Markl received his PhD in computer science under the direction of Rudolf Bayer at the Technical University of Munich. His doctoral research led to the development of the UB-Tree. From 1997 to 2000, he was research group leader at FORWISS, the Bavarian research center for knowledge-based systems. From 2001 to 2008, he was project leader at the IBM Almaden Research Center, Silicon Valley. Since 2008, he has been full professor and Chair of the Database Systems and Information Management Group at the Technical University of Berlin. Since 2014, he is head of the Intelligent Analytics for Massive Data Research Department at the German Research Centre for Artificial Intelligence (DFKI), Berlin. From 2014 to 2020, he was director of the Berlin Big Data Center (BBDC). From 2018 to 2020, he was co-director of the Berlin Machine Learning Center (BZML). Together with Klaus-Robert Müll ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]