2 citations · 4 across the 6 of their papers we have counts for
9 papers
LLMs Between the Nodes: Community Discovery Beyond Vectors
Ekta Gujral, Apurva Sinha
Community detection in social network graphs plays a vital role in uncovering group dynamics, influence pathways, and the spread of information. Traditional methods focus primarily…
CPR: Leveraging LLMs for Topic and Phrase Suggestion to Facilitate Comprehensive Product Reviews
Ekta Gujral, Apurva Sinha, Lishi Ji +1
Consumers often heavily rely on online product reviews, analyzing both quantitative ratings and textual descriptions to assess product quality. However, existing research hasn't ad…
PAE: LLM-based Product Attribute Extraction for E-Commerce Fashion Trends
Apurva Sinha, Ekta Gujral
Product attribute extraction is an growing field in e-commerce business, with several applications including product ranking, product recommendation, future assortment planning and…
Modeling and Mining Multi-Aspect Graphs With Scalable Streaming Tensor Decomposition
Ekta Gujral
Graphs emerge in almost every real-world application domain, ranging from online social networks all the way to health data and movie viewership patterns. Typically, such real-worl…
Adaptive Granularity in Tensors: A Quest for Interpretable Structure
Ravdeep Pasricha, Ekta Gujral, Evangelos E. Papalexakis
Data collected at very frequent intervals is usually extremely sparse and has no structure that is exploitable by modern tensor decomposition algorithms. Thus the utility of such t…
OCTen: Online Compression-based Tensor Decomposition
Ekta Gujral, Ravdeep Pasricha, Tianxiong Yang +1
Tensor decompositions are powerful tools for large data analytics as they jointly model multiple aspects of data into one framework and enable the discovery of the latent structure…
t-PINE: Tensor-based Predictable and Interpretable Node Embeddings
Saba A. Al-Sayouri, Ekta Gujral, Danai Koutra +2
Graph representations have increasingly grown in popularity during the last years. Existing representation learning approaches explicitly encode network structure. Despite their go…
Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition
Ravdeep Pasricha, Ekta Gujral, Evangelos E. Papalexakis
Tensor decompositions are used in various data mining applications from social network to medical applications and are extremely useful in discovering latent structures or concepts…
SamBaTen: Sampling-based Batch Incremental Tensor Decomposition
Ekta Gujral, Ravdeep Pasricha, Evangelos E. Papalexakis
Tensor decompositions are invaluable tools in analyzing multimodal datasets. In many real-world scenarios, such datasets are far from being static, to the contrary they tend to gro…