Category Archives: nlp

User Specific Word Vectors-Customized on Climate Data

Here in this article, two ways are presented to self-train word vectors. This is highly useful if you do not wish to use word vectors trained on Wikipedia or twitter or so datasets. You can load your data file and make your own model, this model can be saved for future work. This has theContinue reading “User Specific Word Vectors-Customized on Climate Data”

Word2vec and the distance between words based on it

This is a short article to show how the distance between words can be computed using word2vec. I often follow deep theoretical and large practical articles with small articles covering basics. Even basics are important and hence here today is a small article on how to compute the distance between words with help of word2vec.Continue reading “Word2vec and the distance between words based on it”

360 degree Test for Intelligence for Machines

Note: This article appears in full text on researchgate at following link in original: (PDF) 360 degree Test for Intelligence for Machines (researchgate.net) [ https://www.researchgate.net/publication/366824869_360_degree_Test_for_Intelligence_for_Machines%5D Turing Test, is one of the most famous test to declare intelligence of a machine. Turning test had several variations and characterizations to study. The most popular version of Turning test involveContinue reading “360 degree Test for Intelligence for Machines”

Fuzzy Rough Set based Evaluations of Summaries

Note: This same article appears in my median.com account as well #AI-EXERCISE #RESEARCH-Excercise This short article lays emphasis on how to evaluate summaries produced from Text Summarization. The toolkit used here is Fuzzy Rough sets. The reference summary and the system summary are evaluated and compared for similarity using Fuzzy Rough Set based lower similarityContinue reading “Fuzzy Rough Set based Evaluations of Summaries”

Redefining Natural Language Processing Evaluation Techniques

Nidhika Yadav Note: This same article appears in my median.com account as well and possibly on researchgate.com as well Abstract- There is a profound need to build robust evaluation techniques for NLP tasks. The current evaluation techniques are quite old while the algorithm they evaluate are the latest state of art methods. Hence, there isContinue reading “Redefining Natural Language Processing Evaluation Techniques”

Soft Rough Sets based Summarization Models — Part 2 (Approximate Learning)

Note: This same article appears in my median.com account as well In the last article we discussed, on how Soft Sets, a tool for uncertainity handling can be used for summarization of text data. We emphasized the role of WordCloud in this as well. In previous article, Soft set was defined as: Definition 1: [Molodtsov 1999]Continue reading “Soft Rough Sets based Summarization Models — Part 2 (Approximate Learning)”

Soft Set Based Summarization Model

(Applications of Approximate Learning) Nidhika Yadav Soft set basically deal with uncertain data which is not precisely classified into one domain of required characterization. Note one domain may be approximate while in another domain of knowledge the same problem may be precise. This can be understood as political parties example, in one domain a politicalContinue reading “Soft Set Based Summarization Model”

Artificial Intelligence in Education

AI in Education is opening its avenues and wings of AI are flying high over the entire education sector from primary to high schools, graduate and more levels. Right now, even ICT based education is not fully used to grassroot levels, yet its significance can’t be ruled out. However, Internet and communication technologies are notContinue reading “Artificial Intelligence in Education”

Handling Missing Values in Data in Python

Handling missing value in data is crucial. Questions arise how to deal with it, given a empty, Null, or large positive and large negative value are not easy to handle. How to use these values then, how to process the data after that. Some people deal with missing values by removing the rows or tuplesContinue reading “Handling Missing Values in Data in Python”

Now is time of AI based Sound Embeddings

Yes sound is where Artificial Intelligence needs to get in more deeper, given there are powerful language models, advanced image and text embeddings. Getting to have embeddings of sound is the next level of success, as per my suggestions. This is the latest in getting an AI based new name to a new born baby,Continue reading “Now is time of AI based Sound Embeddings”