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Citation Graph
A citation graph (or citation network), in information science and bibliometrics, is a directed graph that describes the citations within a collection of documents. Each vertex (or node) in the graph represents a document in the collection, and each edge is directed from one document toward another that it cites (or vice versa depending on the specific implementation). Citation graphs have been utilised in various ways, including forms of citation analysis, academic search tools and court judgements. They are predicted to become more relevant and useful in the future as the body of published research grows. Implementation There is no standard format for the citations in bibliographies, and the record linkage of citations can be a time-consuming and complicated process. Furthermore, citation errors can occur at any stage of the publishing process. However, there is a long history of creating citation databases, also known as citation indexes, so there is a lot of information ...
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Machine-readable Data
Machine-readable data, or computer-readable data, is data in a format that can be processed by a computer. Machine-readable data must be structured data. Attempts to create machine-readable data occurred as early as the 1960s. At the same time that seminal developments in machine-reading and natural-language processing were releasing (like Weizenbaum's ELIZA), people were anticipating the success of machine-readable functionality and attempting to create machine-readable documents. One such example was musicologist Nancy B. Reich's creation of a machine-readable catalog of composer William Jay Sydeman's works in 1966. In the United States, the OPEN Government Data Act of 14 January 2019 defines machine-readable data as "data in a format that can be easily processed by a computer without human intervention while ensuring no semantic meaning is lost." The law directs U.S. federal agencies to publish public data in such a manner, ensuring that "any public data asset of the agency ...
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Collaboration Graph
In mathematics and social science, a collaboration graph is a graph modeling some social network where the vertices represent participants of that network (usually individual people) and where two distinct participants are joined by an edge whenever there is a collaborative relationship between them of a particular kind. Collaboration graphs are used to measure the closeness of collaborative relationships between the participants of the network. Types considered in the literature The most well-studied collaboration graphs include: *Collaboration graph of mathematicians also known as the Erdős collaboration graph, where two mathematicians are joined by an edge whenever they co-authored a paper together (with possibly other co-authors present). *Collaboration graph of movie actors, also known as the Hollywood graph or co-stardom network, where two movie actors are joined by an edge whenever they appeared in a movie together. *Collaborations graphs in other social networks, such as s ...
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Collaboration Graph
In mathematics and social science, a collaboration graph is a graph modeling some social network where the vertices represent participants of that network (usually individual people) and where two distinct participants are joined by an edge whenever there is a collaborative relationship between them of a particular kind. Collaboration graphs are used to measure the closeness of collaborative relationships between the participants of the network. Types considered in the literature The most well-studied collaboration graphs include: *Collaboration graph of mathematicians also known as the Erdős collaboration graph, where two mathematicians are joined by an edge whenever they co-authored a paper together (with possibly other co-authors present). *Collaboration graph of movie actors, also known as the Hollywood graph or co-stardom network, where two movie actors are joined by an edge whenever they appeared in a movie together. *Collaborations graphs in other social networks, such as s ...
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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 ...
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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 ...
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Index Term
In information retrieval, an index term (also known as subject term, subject heading, descriptor, or keyword) is a term that captures the essence of the topic of a document. Index terms make up a controlled vocabulary for use in bibliographic records. They are an integral part of bibliographic control, which is the function by which libraries collect, organize and disseminate documents. They are used as keywords to retrieve documents in an information system, for instance, a catalog or a search engine. A popular form of keywords on the web are tags, which are directly visible and can be assigned by non-experts. Index terms can consist of a word, phrase, or alphanumerical term. They are created by analyzing the document either manually with subject indexing or automatically with automatic indexing or more sophisticated methods of keyword extraction. Index terms can either come from a controlled vocabulary or be freely assigned. Keywords are stored in a search index. Common words li ...
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Depth-first Search
Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking. Extra memory, usually a stack, is needed to keep track of the nodes discovered so far along a specified branch which helps in backtracking of the graph. A version of depth-first search was investigated in the 19th century by French mathematician Charles Pierre Trémaux as a strategy for solving mazes. Properties The time and space analysis of DFS differs according to its application area. In theoretical computer science, DFS is typically used to traverse an entire graph, and takes time where , V, is the number of vertices and , E, the number of edges. This is linear in the size of the graph. In these applications it also uses space O(, V, ) in the worst case to store the stack of vertices on th ...
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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 ...
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Citation Impact
Citation impact is a measure of how many times an academic journal article or book or author is cited by other articles, books or authors. Citation counts are interpreted as measures of the impact or influence of academic work and have given rise to the field of bibliometrics or scientometrics, specializing in the study of patterns of academic impact through citation analysis. The journal impact factor, the two-year average ratio of citations to articles published, is a measure of the importance of journals. It is used by academic institutions in decisions about academic tenure, promotion and hiring, and hence also used by authors in deciding which journal to publish in. Citation-like measures are also used in other fields that do ranking, such as Google's PageRank algorithm, software metrics, college and university rankings, and business performance indicators. Article-level One of the most basic citation metrics is how often an article was cited in other articles, books, or o ...
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Classification System
Classification is a process related to categorization, the process in which ideas and objects are recognized, differentiated and understood. Classification is the grouping of related facts into classes. It may also refer to: Business, organizations, and economics * Classification of customers, for marketing (as in Master data management) or for profitability (e.g. by Activity-based costing) * Classified information, as in legal or government documentation * Job classification, as in job analysis * Standard Industrial Classification, economic activities Mathematics * Attribute-value system, a basic knowledge representation framework * Classification theorems in mathematics * Mathematical classification, grouping mathematical objects based on a property that all those objects share * Statistical classification, identifying to which of a set of categories a new observation belongs, on the basis of a training set of data Media * Classification (literature), a figure of speec ...
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Self-organizing
Self-organization, also called spontaneous order in the social sciences, is a process where some form of overall order arises from local interactions between parts of an initially disordered system. The process can be spontaneous when sufficient energy is available, not needing control by any external agent. It is often triggered by seemingly random fluctuations, amplified by positive feedback. The resulting organization is wholly decentralized, distributed over all the components of the system. As such, the organization is typically robust and able to survive or self-repair substantial perturbation. Chaos theory discusses self-organization in terms of islands of predictability in a sea of chaotic unpredictability. Self-organization occurs in many physical, chemical, biological, robotic, and cognitive systems. Examples of self-organization include crystallization, thermal convection of fluids, chemical oscillation, animal swarming, neural circuits, and black market ...
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