Link Analysis
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Link Analysis
In network theory, link analysis is a data-analysis technique used to evaluate relationships (connections) between nodes. Relationships may be identified among various types of nodes (objects), including organizations, people and transactions. Link analysis has been used for investigation of criminal activity (fraud detection, counterterrorism, and intelligence), computer security analysis, search engine optimization, market research, medical research, and art. Knowledge discovery Knowledge discovery is an iterative and interactive process used to identify, analyze and visualize patterns in data. Network analysis, link analysis and social network analysis are all methods of knowledge discovery, each a corresponding subset of the prior method. Most knowledge discovery methods follow these steps (at the highest level): # Data processing # Transformation # Analysis # Visualization Data gathering and processing requires access to data and has several inherent issues, including in ...
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Network Theory
Network theory is the study of graphs as a representation of either symmetric relations or asymmetric relations between discrete objects. In computer science and network science, network theory is a part of graph theory: a network can be defined as a graph in which nodes and/or edges have attributes (e.g. names). Network theory has applications in many disciplines including statistical physics, particle physics, computer science, electrical engineering, biology, archaeology, economics, finance, operations research, climatology, ecology, public health, sociology, and neuroscience. Applications of network theory include logistical networks, the World Wide Web, Internet, gene regulatory networks, metabolic networks, social networks, epistemological networks, etc.; see List of network theory topics for more examples. Euler's solution of the Seven Bridges of Königsberg problem is considered to be the first true proof in the theory of networks. Network optimization Network pr ...
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Data Processing
Data processing is the collection and manipulation of digital data to produce meaningful information. Data processing is a form of ''information processing'', which is the modification (processing) of information in any manner detectable by an observer.Data processing is distinct from ''word processing'', which is manipulation of text specifically rather than data generally. The term "Data Processing", or "DP" has also been used to refer to a department within an organization responsible for the operation of data processing programs. Data processing functions Data processing may involve various processes, including: * Validation – Ensuring that supplied data is correct and relevant. * Sorting – "arranging items in some sequence and/or in different sets." * Summarization(statistical) or (automatic) – reducing detailed data to its main points. * Aggregation – combining multiple pieces of data. * Analysis – the "collection, organization, an ...
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Association Matrix
Association may refer to: *Club (organization), an association of two or more people united by a common interest or goal *Trade association, an organization founded and funded by businesses that operate in a specific industry *Voluntary association, a body formed by individuals to accomplish a purpose, usually as volunteers Association in various fields of study *Association (archaeology), the close relationship between objects or contexts. *Association (astronomy), combined or co-added group of astronomical exposures * Association (chemistry) *Association (ecology), a type of ecological community *Genetic association, when one or more genotypes within a population co-occur * Association (object-oriented programming), defines a relationship between classes of objects *Association (psychology), a connection between two or more concepts in the mind or imagination *Association (statistics), a statistical relationship between two variables *File association, associates a file with a ...
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Hawala
Hawala or hewala ( ar, حِوالة , meaning ''transfer'' or sometimes ''trust''), also known as in Persian, and or in Somali, is a popular and informal value transfer system based on the performance and honour of a huge network of money brokers (known as ''hawaladars''). They operate outside of, or parallel to, traditional banking, financial channels and remittance systems. The system requires a minimum of two hawaladars that take care of the "transaction" without the movement of cash or telegraphic transfer. While hawaladars are spread throughout the world, they are primarily located in the Middle East, North Africa, the Horn of Africa and the Indian subcontinent. Hawala follows Islamic traditions but its use is not limited to Muslims. Origins The hawala system originated in India. Hawala as a legal concept came to be described as early as 1327, according to Schramm and Taube, though the actual practice has existed since the 8th century between Indian, Arab and Muslim ...
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Network Charts
A project network diagram is a graph that displays the order in which a project’s activities are to be completed. Derived from the work breakdown structure, the terminal elements of a project are organized sequentially based on the relationship among them. It is typically drawn from left to right to reflect project chronology. Techniques Activity-on-Node The Activity-on-Node (AON) technique uses nodes to represent individual project activities and path arrows to designate the sequence of activity completion. Nodes are labelled using information pertaining to the activity. According to Project Management, nodes should at least display the following information: * Identifier * Descriptive label * Activity duration * Early start time * Early finish time * Late start time * Late finish time * Activity float (slack) Start and finish times are used to determine the critical path of a project. Activity float, or slack, time is used in project crashing. Other techniq ...
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Visualization (computer Graphics)
Visualization or visualisation (see spelling differences) is any technique for creating images, diagrams, or animations to communicate a message. Visualization through visual imagery has been an effective way to communicate both abstract and concrete ideas since the dawn of humanity. Examples from history include cave paintings, Egyptian hieroglyphs, Greek geometry, and Leonardo da Vinci's revolutionary methods of technical drawing for engineering and scientific purposes. Visualization today has ever-expanding applications in science, education, engineering (e.g., product visualization), interactive multimedia, medicine, etc. Typical of a visualization application is the field of computer graphics. The invention of computer graphics (and 3D computer graphics) may be the most important development in visualization since the invention of central perspective in the Renaissance period. The development of animation also helped advance visualization. Overview The use of visual ...
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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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Breadth-first Search
Breadth-first search (BFS) is an algorithm for searching a tree data structure for a node that satisfies a given property. It starts at the tree root and explores all nodes at the present depth prior to moving on to the nodes at the next depth level. Extra memory, usually a queue, is needed to keep track of the child nodes that were encountered but not yet explored. For example, in a chess endgame a chess engine may build the game tree from the current position by applying all possible moves, and use breadth-first search to find a win position for white. Implicit trees (such as game trees or other problem-solving trees) may be of infinite size; breadth-first search is guaranteed to find a solution node if one exists. In contrast, (plain) depth-first search, which explores the node branch as far as possible before backtracking and expanding other nodes, may get lost in an infinite branch and never make it to the solution node. Iterative deepening depth-first search avoids ...
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Dijkstra's Algorithm
Dijkstra's algorithm ( ) is an algorithm for finding the shortest paths between nodes in a graph, which may represent, for example, road networks. It was conceived by computer scientist Edsger W. Dijkstra in 1956 and published three years later. The algorithm exists in many variants. Dijkstra's original algorithm found the shortest path between two given nodes, but a more common variant fixes a single node as the "source" node and finds shortest paths from the source to all other nodes in the graph, producing a shortest-path tree. For a given source node in the graph, the algorithm finds the shortest path between that node and every other. It can also be used for finding the shortest paths from a single node to a single destination node by stopping the algorithm once the shortest path to the destination node has been determined. For example, if the nodes of the graph represent cities and edge path costs represent driving distances between pairs of cities connected by a dir ...
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Information Overload
Information overload (also known as infobesity, infoxication, information anxiety, and information explosion) is the difficulty in understanding an issue and effectively making decisions when one has too much information (TMI) about that issue, and is generally associated with the excessive quantity of daily information. The term "information overload" was first used as early as 1962 by scholars in management and information studies, including in Bertram Gross' 1964 book, ''The Managing of Organizations,'' and was further popularized by Alvin Toffler in his bestselling 1970 book ''Future Shock.'' Speier et al. (1999) said that if input exceeds the processing capacity, information overload occurs, which is likely to reduce the quality of the decisions. In a newer definition, Roetzel (2019) focuses on time and resources aspects. He states that when a decision-maker is given many sets of information, such as complexity, amount, and contradiction, the quality of its decision is decre ...
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