Saroj Kaushik


2017

pdf
SemTagger: A Novel Approach for Semantic Similarity Based Hashtag Recommendation on Twitter
Kuntal Dey | Ritvik Shrivastava | Saroj Kaushik | L Venkata Subramaniam
Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017)

2016

pdf
A Paraphrase and Semantic Similarity Detection System for User Generated Short-Text Content on Microblogs
Kuntal Dey | Ritvik Shrivastava | Saroj Kaushik
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers

Existing systems deliver high accuracy and F1-scores for detecting paraphrase and semantic similarity on traditional clean-text corpus. For instance, on the clean-text Microsoft Paraphrase benchmark database, the existing systems attain an accuracy as high as 0:8596. However, existing systems for detecting paraphrases and semantic similarity on user-generated short-text content on microblogs such as Twitter, comprising of noisy and ad hoc short-text, needs significant research attention. In this paper, we propose a machine learning based approach towards this. We propose a set of features that, although well-known in the NLP literature for solving other problems, have not been explored for detecting paraphrase or semantic similarity, on noisy user-generated short-text data such as Twitter. We apply support vector machine (SVM) based learning. We use the benchmark Twitter paraphrase data, released as a part of SemEval 2015, for experiments. Our system delivers a paraphrase detection F1-score of 0.717 and semantic similarity detection F1-score of 0.741, thereby significantly outperforming the existing systems, that deliver F1-scores of 0.696 and 0.724 for the two problems respectively. Our features also allow us to obtain a rank among the top-10, when trained on the Microsoft Paraphrase corpus and tested on the corresponding test data, thereby empirically establishing our approach as ubiquitous across the different paraphrase detection databases.

2004

pdf
Information Extraction from Hindi Texts
Kamlesh Dutta | Saroj Kaushik | Nupur Prakash
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)