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MNHN-Tree-Tools: MNHN-Tree-Tools is an opensource phylogenetics inference software working on nucleic and protein sequences. Clustering of DNA or protein sequences and phylogenetic tree inference from a set of sequences. At the core it employs a distance-density based approach. Thomas Haschka, Loïc Ponger, Christophe Escudé and Julien ...
Tag cloud of a mailing list [1] A tag cloud with terms related to Web 2.0. A tag cloud (also known as a word cloud or weighted list in visual design) is a visual representation of text data which is often used to depict keyword metadata on websites, or to visualize free form text.
A co-occurrence network created with KH Coder. Co-occurrence network, sometimes referred to as a semantic network, [1] is a method to analyze text that includes a graphic visualization of potential relationships between people, organizations, concepts, biological organisms like bacteria [2] or other entities represented within written material.
Word clustering is a different approach to the induction of word senses. It consists of clustering words, which are semantically similar and can thus bear a specific meaning. Lin’s algorithm [ 5 ] is a prototypical example of word clustering, which is based on syntactic dependency statistics, which occur in a corpus to produce sets of words ...
PlantUML is an open-source tool allowing users to create diagrams from a plain text language. Besides various UML diagrams, PlantUML has support for various other software development related formats (such as Archimate, Block diagram, BPMN, C4, Computer network diagram, ERD, Gantt chart, Mind map, and WBD), as well as visualisation of JSON and YAML files.
A cluster in general is a group or bunch of several discrete items that are close to each other. The cluster diagram figures a cluster, such as a network diagram figures a network, a flow diagram a process or movement of objects, and a tree diagram an abstract tree. But all these diagrams can be considered interconnected: A network diagram can ...
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A keyword clustering tool scans the list of keywords and then picks the most popular keyword. The most popular keyword is a keyword with the highest search volume.Then a tool compares the TOP 10 search result listings that showed up for the taken keyword to the TOP10 search results that showed up for another keyword to detect the number of matching URLs.
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