LISP
According to Wikipedia, “A kangaroo word is a word that contains letters of another word, in order, with the same meaning. For example: the word ‘masculine’ contains the word ‘male’, which is a synonym of the first word; similarly, the word ‘observe’ contains its synonym ‘see’.” Interesting idea. The key point to note is that […]
Detecting sentiments and emotions in a piece of text are frequently performed activities in Text analysis. There are some API services available for this. For example, meaningcloud.com has an API for detecting sentiments in the text submitted to it. Another API service provider is aylien.com . Emotion detection for text is supported by qemotion.com. Because […]
I had earlier briefly talked about the Ilexicon project that I have been working on for some time now. The goal is to build an intelligent dictionary that will come in handy while implementing NLP applications such as recognizers and generators. In today’s post, I want to demonstrate some cool features available in iLexicon. At present iLexicon […]
If you are into writing poems, stories or essays, or you just have a fascination for words, I encourage you to take a look at Datamuse. Recently I was studying about the structure of various poetic forms, and in the process of browing different sites, I stumbled upon Datamuse. I found it to be pretty […]
One of the advanced features of iLangGen is the ability to embed arbitrary function calls on the RHS of grammar rules. Such functions impart interesting dynamic behaviour to the generated data. For convenience and flexibility, iLangGen supports two types of function calls – Direct and Indirect. In the case of the Direct function call, the […]
In the last post, we saw how iLangGen text generation framework supports reuse of grammars through inheritance, akin to object-oriented languages. The good news is that we can achieve reuse through composition as well. The following is a simple grammar, nothing fancy to elaborate. Here is the output when you traverse the grammar without AST. […]
We are familiar with the advantages of class inheritance in object-oriented languages such as C++, C#, Java, and Python. The ability to reuse functionality via inheritance allows us to express our software design optimally, without having to write redundant code. iLangGen encourages the reuse of grammars by supporting Grammar Inheritance, where a grammar can explicitly […]
Many times, we need to repeatedly generate an element, or in general, have a way to control the number times one or more elements get generated. iLangGen supports all the standard cases: – Zero or once – Zero or more times (unbounded) – Zero or more times (bounded) – One or more times (unbounded) – […]
The two primary areas in Natural Language processing are Natural Language Understanding and Natural Language Generation. The former is concerned with processing and making sense of natural language text, whereas the latter is concerned with synthesizing text, possibly from some deep representation. Both are fascinating and at the same time, challenging, areas of research. The […]
Recent Comments