2 citations · 3 across the 3 of their papers we have counts for
5 papers
Fine-grained large-scale content recommendations for MSX sellers
Manpreet Singh, Ravdeep Pasricha, Ravi Prasad Kondapalli +6
One of the most critical tasks of Microsoft sellers is to meticulously track and nurture potential business opportunities through proactive engagement and tailored solutions. Recom…
High Significant Fault Detection in Azure Core Workload Insights
Pranay Lohia, Laurent Boue, Sharath Rangappa +1
Azure Core workload insights have time-series data with different metric units. Faults or Anomalies are observed in these time-series data owing to faults observed with respect to…
A case study of Generative AI in MSX Sales Copilot: Improving seller productivity with a real-time question-answering system for content recommendation
Manpreet Singh, Ravdeep Pasricha, Nitish Singh +4
In this paper, we design a real-time question-answering system specifically targeted for helping sellers get relevant material/documentation they can share live with their customer…
Searching, fast and slow, through product catalogs
Dayananda Ubrangala, Juhi Sharma, Sharath Kumar Rangappa +3
String matching algorithms in the presence of abbreviations, such as in Stock Keeping Unit (SKU) product catalogs, remains a relatively unexplored topic. In this paper, we present…
Improving search relevance of Azure Cognitive Search by Bayesian optimization
Nitin Agarwal, Ashish Kumar, Kiran R +2
Azure Cognitive Search (ACS) has emerged as a major contender in "Search as a Service" cloud products in recent years. However, one of the major challenges for ACS users is to impr…