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Lilian is a chatterbot (or a chatterbot algorithm) written in Java which focuses on fast response, given a training corpus

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Lilian

Lilian is a chatterbot (or a chatterbot algorithm) written in Java which focuses on fast response, given a training corpus. Lilian has been developed by Martí-Joan Nogué Coll. It started as a "small" project that used around 1000 if clasuses (that's madness huh?) as he was learning his first programming language. Years have passed and Lilian has become a litlle bit more intelligent.

How Lilian works

The corpus.dat contains a set of questions-answer that Lilian uses as a hint to answer. Basically what she does is to retrieve the user's question, split it into words and for every word:

for every word do
	check in corpus all questions that have this word
	probability is 1/number_questions_with_word
	add this answer (if not already) into an array and add the probabilty to a counter variable.
endfor

Pick answer with highest probability

This algorithm exhaustively iterates through the corpus and so we need a way to access its data as fast as possible. And the answer to that is by using a Double Ternary Search Tree (DTST). A DTST is a normal TST but where every node has another TST.

Installing Lilian

The easiest way to install lilian is by downloading all files located inside the netbeans folder and place them wherever you want. Then open Netbeans and select open existing project and select the downloaded files.

Java classes

If you want to compile Lilian with a different method, download the java classes files. You can start a project with a different IDE (like Eclipse) and import this files.

More information

If you want to know more about Lilian, visit catsoft-studios.com/projects and click on the Lilian project. You will be redirected to a series of articles we wrote where it is explained how Lilian works. If you have any questions, you can contact us at catsoft.studios gmail.

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Lilian is a chatterbot (or a chatterbot algorithm) written in Java which focuses on fast response, given a training corpus

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