GNOWSYS, Gnowledge Networking and Organizing System, is a web based hybrid gnowledge base with a kernel for semantic computing. It is developed in Python and works as an installed product in ZOPE.
Piggydb is a flexible and scalable knowledge building platform that supports a heuristic or bottom-up approach to discover new concepts or ideas based on your input. You can begin with using it as a flexible outliner, diary or notebook, and as your database grows, Piggydb helps you to shape or elaborate your own knowledge.
The proliferation of the internet has caused the process of browsing and searching for information to become extremely cumbersome. While many search engines provide reasonable information, they still fall short by overwhelming users with a multitude of often irrelevant results.
We present the
... [More] Automatic Concept Extraction (ACE) algorithm, which can aid users performing searches using search engines. We discuss ACE both theoretically, and in the context of a Graphical User Interface and implementation which we have constructed in java to aid in qualitatively evaluating our algorithm. ACE is found to perform at least as well or better than 4 other related algorithms which we survey in the literature. [Less]
FCAAPI is an API for Formal Concept Analysis (FCA) tool developpers. It is an initiative to set standards for FCA tools for better interoperability. FCAAPI is implemented by the open-source library FCAlib. Javadoc for FCAAPI can be accessed here.
FCAlib is an open-source, extensible library for Formal Concept Analysis (FCA) tool developers that implements the FCAAPI. It provides basic functionalities that are needed for building an FCA tool. It supports incomplete contexts and includes efficient implementations of basic FCA algorithms like
... [More] implicational closure, next-closed set, etc. It implements the attribute exploration algorithm in such a way that it can be used together with a custom implemented expert that supports FCAAPI. Javadoc for FCAlib can be found here.
FCAlib is extended by OntoComPlib for using attribute exploration together with OWL ontologies.
The following code segment shows how to create a formal context, add attributes to it, create an expert for this context, and start attribute exploration:
// Create a formal context whose attributes are of type String, and whose objects have
// identifiers of type String
FormalContext context = new FormalContext();
// Create an expert for this context
MyExpertClass expert = new MyExpertClass(context);
// Add attributes to this context
context.addAttribute("a");
context.addAttribute("b");
context.addAttribute("c");
// Set expert for this context
context.setExpert(expert);
// Context listens to the actions of the expert
expert.addExpertActionListener(context);
// Create an expert action for starting attribute exploration
StartExplorationAction> action =
new StartExplorationAction>();
action.setContext(context);
// Fire the action, exploration starts...
expert.fireExpertAction(action);The following code segment shows how to create a set of implications for the above context, add implications to it, and compute next-closure:
// Create a set of implications for the above context. Attributes are of type String
ImplicationSet = new ImplicationSet(context);
// Create a new implication with empty premise and conclusion
Implication imp = new Implication();
// Add attribute "a" to the premise
imp.getPremise().add("a");
// Add attribute "b" to the conclusion
imp.getConclusion().add("b");
// Add this implication to the implication set
implications.add(imp);
// Compute the next-closed set after mySet, and update mySet
mySet = implications.nextClosure(mySet);For more examples please see the test package in the source. [Less]
limada::concept
is an application to draw, edit and store concept maps. A concept map is a diagram showing the relationships among concepts. They are graphical tools for organizing and representing knowledge. They include concepts, usually enclosed in circles or boxes of some type, and
... [More] relationships between concepts indicated by a connecting line linking two concepts.
Concept maps are similar to mindmaps, but give more freedom, as mindmaps are often restricted to radial hierarchies and tree structures.
limada::framework
is a framework for managing relationships of data in non-hierarchical structures, where the individual elements are interconnected in complex ways. The philosophy behind: Information is connection, is relationship of data. [Less]
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