Information Retrieval with tf-idf #climate_data

Here in this short article, we analyze Information Retrieval of documents using tf-idf technique. Though this technique is not that popular, but it for sure in parts is backbone of many algorithms. Now, with deep learning this technique has been sidelined, but, none the less, it is the key session of Information Retrieval research. TheContinue reading “Information Retrieval with tf-idf #climate_data”

Sentiment Analysis of Climate Text Data – Lesson 4

In this article, we shall see how climate text data collected and computed for analysis in previous articles can be analyzed for sentiment analysis. The toolkit used today for text sentiment analysis is TextBlob. There are several other ways to compute sentiments. But the steps shall be the same though the libraries can change. Lets usContinue reading “Sentiment Analysis of Climate Text Data – Lesson 4”

Climate Data- NLP-based Textual Analysis- Part 2

The dataset taken had 66 files and with total number of words being 97099. We know this dataset is small, given the topic is so important, but with our resources and web crawling of important websites, this much was collected. This can be taken as a nice sample over the big data available on web.Continue reading “Climate Data- NLP-based Textual Analysis- Part 2”

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”

Predicting Preferred Working Hours with RNN GRU

In this article, we propose to predict the preferred working hours by individuals based on the present inputs provided. Why this is required? As the work is preset and work goals are made based on resource predictions. Employees are resources of an organization and if we accumulate current phenomena with time we can predict wellContinue reading “Predicting Preferred Working Hours with RNN GRU”

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 ( [ 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 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”

Quick Soft Reduct – Feature Selection with Soft Rough Sets

Note: This same article appears in my account as well and possibly on as well #Research_Excercise #ReseachProject #AI-Excercise This article provides the algorithm for feature selection using Soft Rough Sets called Soft Quick Reduct. These techniques are based on Soft Rough Sets, a new technique to study the relationship in smaller datasets. TheContinue reading “Quick Soft Reduct – Feature Selection with Soft Rough Sets”

Redefining Natural Language Processing Evaluation Techniques

Nidhika Yadav Note: This same article appears in my account as well and possibly on 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”