Aika (software) References Navigation menuwww.aika-software.org"The Aika Algorithm for Text Mining and...
Data mining and machine learning softwareFree computer librariesFree science softwareKnowledge representationNatural language processing toolkitsNeural network softwareCross-platform softwareJava (programming language)Free software programmed in Java (programming language)Linguistic research software
Apache licenseAIartificial neural networksfrequent pattern miningexpert systemstext analysisnon-monotonic logictext annotationneuronslattice
| Developer(s) | Aika Project |
|---|---|
| Stable release | 0.5 / June 1, 2017 (2017-06-01) |
| Written in | Java |
| Operating system | Cross-platform |
| Type | Text mining and Information extraction |
| License | Apache license |
| Website | www.aika-software.org |
Aika[1] is an open source text mining engine. It can automatically extract and annotate semantic information into text. In case this information is ambiguous, Aika will generate several hypothetical interpretations concerning the meaning of the text and pick the most likely one. Aika is written in Java and distributed under the Apache license.
The Aika algorithm is based on various ideas and approaches from the field of AI such as artificial neural networks, frequent pattern mining and logic based expert systems. It can be applied to a broad spectrum of text analysis tasks and combines these concepts in a single algorithm.
Aika is based on non-monotonic logic, meaning that it first draws tentative conclusions only. In other words, Aika is able to generate multiple mutually exclusive interpretations of a word, phrase, or sentence, and select the most likely interpretation. It does so by propagating activations through a neural network. These activations can be seen as a kind of text annotation since they refer to a specific text segment and a given interpretation.
Aika consists of two layers. The neural layer, containing all the neurons and continuously weighted synapses and underneath that the discrete logic layer, containing a boolean representation of all the neurons. The logic layer uses a frequent pattern lattice to efficiently store the individual logic nodes.
References
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