25 citations · 64 across the 6 of their papers we have counts for
7 papers
Word Similarity Datasets for Indian Languages: Annotation and Baseline Systems
Syed S. Akhtar, Arihant Gupta, Avijit Vajpayee +2
With the advent of word representations, word similarity tasks are becoming increasing popular as an evaluation metric for the quality of the representations. In this paper, we pre…
Gender Prediction in English-Hindi Code-Mixed Social Media Content : Corpus and Baseline System
Ankush Khandelwal, Sahil Swami, Syed Sarfaraz Akhtar +1
The rapid expansion in the usage of social media networking sites leads to a huge amount of unprocessed user generated data which can be used for text mining. Author profiling is t…
Humor Detection in English-Hindi Code-Mixed Social Media Content : Corpus and Baseline System
Ankush Khandelwal, Sahil Swami, Syed S. Akhtar +1
The tremendous amount of user generated data through social networking sites led to the gaining popularity of automatic text classification in the field of computational linguistic…
A Corpus of English-Hindi Code-Mixed Tweets for Sarcasm Detection
Sahil Swami, Ankush Khandelwal, Vinay Singh +2
Social media platforms like twitter and facebook have be- come two of the largest mediums used by people to express their views to- wards different topics. Generation of such large…
An English-Hindi Code-Mixed Corpus: Stance Annotation and Baseline System
Sahil Swami, Ankush Khandelwal, Vinay Singh +2
Social media has become one of the main channels for peo- ple to communicate and share their views with the society. We can often detect from these views whether the person is in f…
An Unsupervised Approach for Mapping between Vector Spaces
Syed Sarfaraz Akhtar, Arihant Gupta, Avijit Vajpayee +3
We present a language independent, unsupervised approach for transforming word embeddings from source language to target language using a transformation matrix. Our model handles t…
Unsupervised Morphological Expansion of Small Datasets for Improving Word Embeddings
Syed Sarfaraz Akhtar, Arihant Gupta, Avijit Vajpayee +2
We present a language independent, unsupervised method for building word embeddings using morphological expansion of text. Our model handles the problem of data sparsity and yields…