4 citations · 10 across the 11 of their papers we have counts for
13 papers
Noise in Relation Classification Dataset TACRED: Characterization and Reduction
Akshay Parekh, Ashish Anand, Amit Awekar
The overarching objective of this paper is two-fold. First, to explore model-based approaches to characterize the primary cause of the noise. in the RE dataset TACRED Second, to id…
Budget Sensitive Reannotation of Noisy Relation Classification Data Using Label Hierarchy
Akshay Parekh, Ashish Anand, Amit Awekar
Large crowd-sourced datasets are often noisy and relation classification (RC) datasets are no exception. Reannotating the entire dataset is one probable solution however it is not…
Are Word Embedding Methods Stable and Should We Care About It?
Angana Borah, Manash Pratim Barman, Amit Awekar
A representation learning method is considered stable if it consistently generates similar representation of the given data across multiple runs. Word Embedding Methods (WEMs) are…
Taxonomical hierarchy of canonicalized relations from multiple Knowledge Bases
Akshay Parekh, Ashish Anand, Amit Awekar
This work addresses two important questions pertinent to Relation Extraction (RE). First, what are all possible relations that could exist between any two given entity types? Secon…
Decoding the Style and Bias of Song Lyrics
Manash Pratim Barman, Amit Awekar, Sambhav Kothari
The central idea of this paper is to gain a deeper understanding of song lyrics computationally. We focus on two aspects: style and biases of song lyrics. All prior works to unders…
Fine-grained Entity Recognition with Reduced False Negatives and Large Type Coverage
Abhishek Abhishek, Sanya Bathla Taneja, Garima Malik +2
Fine-grained Entity Recognition (FgER) is the task of detecting and classifying entity mentions to a large set of types spanning diverse domains such as biomedical, finance and spo…
It's Only Words And Words Are All I Have
Manash Pratim Barman, Kavish Dahekar, Abhinav Anshuman +1
The central idea of this paper is to demonstrate the strength of lyrics for music mining and natural language processing (NLP) tasks using the distributed representation paradigm.…
Collective Learning From Diverse Datasets for Entity Typing in the Wild
Abhishek Abhishek, Amar Prakash Azad, Balaji Ganesan +2
Entity typing (ET) is the problem of assigning labels to given entity mentions in a sentence. Existing works for ET require knowledge about the domain and target label set for a gi…
Deep Learning for Detecting Cyberbullying Across Multiple Social Media Platforms
Sweta Agrawal, Amit Awekar
Harassment by cyberbullies is a significant phenomenon on the social media. Existing works for cyberbullying detection have at least one of the following three bottlenecks. First,…
Fine-Grained Entity Type Classification by Jointly Learning Representations and Label Embeddings
Abhishek, Ashish Anand, Amit Awekar
Fine-grained entity type classification (FETC) is the task of classifying an entity mention to a broad set of types. Distant supervision paradigm is extensively used to generate tr…
Batch Incremental Shared Nearest Neighbor Density Based Clustering Algorithm for Dynamic Datasets
Panthadeep Bhattacharjee, Amit Awekar
Incremental data mining algorithms process frequent updates to dynamic datasets efficiently by avoiding redundant computation. Existing incremental extension to shared nearest neig…
Faster K-Means Cluster Estimation
Siddhesh Khandelwal, Amit Awekar
There has been considerable work on improving popular clustering algorithm `K-means' in terms of mean squared error (MSE) and speed, both. However, most of the k-means variants ten…
On Low Overlap Among Search Results of Academic Search Engines
Anasua Mitra, Amit Awekar
Number of published scholarly articles is growing exponentially. To tackle this information overload, researchers are increasingly depending on niche academic search engines. Recen…