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P. Kulkarni

4 papers hereh-index 181.2k citations148 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.DB1
  • cs.IR1
same name
  • P. Kulkarni — 9 papers, h 4
  • P. Kulkarni — 7 papers, h 19
  • P. Kulkarni — 7 papers, h 6
  • P. Kulkarni — 3 papers, h 1
  • P. Kulkarni — 1 paper, h 2
  • P. Kulkarni — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20112023
most citedContextual Mood Analysis with Knowledge Graph Representation for Hindi Song Lyrics in Devanagari Script

3 citations · 5 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CL2023

Thematic context vector association based on event uncertainty for Twitter

Vaibhav Khatavkar, Swapnil Mane, Parag Kulkarni

Keyword extraction is a crucial process in text mining. The extraction of keywords with respective contextual events in Twitter data is a big challenge. The challenging issues are…

cs.CL2021★ 3 cited

Contextual Mood Analysis with Knowledge Graph Representation for Hindi Song Lyrics in Devanagari Script

Makarand Velankar, Rachita Kotian, Parag Kulkarni

Lyrics play a significant role in conveying the song's mood and are information to understand and interpret music communication. Conventional natural language processing approaches…

cs.DB2013

SCAF An effective approach to Classify Subspace Clustering algorithms

Sunita Jahirabadkar, Parag Kulkarni

Subspace clustering discovers the clusters embedded in multiple, overlapping subspaces of high dimensional data. Many significant subspace clustering algorithms exist, each having…

cs.IR2011★ 2 cited

Learning Context for Text Categorization

Y. V. Haribhakta, Dr. Parag Kulkarni

This paper describes our work which is based on discovering context for text document categorization. The document categorization approach is derived from a combination of a learni…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.