Rajyashree Mukherjee

Learn More
One central issue in a long-tail online marketplace such as eBay is to automatically put user self-input items into a catalog in real time. This task is extremely challenging when the inventory scales up, the items become ephemeral, and the user input remains noisy. Indeed, catalog learning has emerged as a key technical property for other major online(More)
We are proposing a new similarity based recommendation system for large-scale dynamic marketplaces. Our solution consists of an offline process, which generates long-term cluster definitions grouping short-lived item listings, and an online system, which utilizes these clusters to first focus on important similarity dimensions and next conducts a trade-off(More)
We present a new algorithm for recommending alternatives to a given item in an e-commerce setting. Our algorithm is an incremental improvement over an earlier system, which recommends similar items by first assigning the input item to clusters and then selecting best quality items within those clusters. The original algorithm does not consider the recent(More)
We present an interactive search assistance agent that integrates search and recommendation-based experiences into a novel unified presentation. The agent guides the user toward more desirable inventory , while also satisfying the constraints that the user constructs with the help of the agent. We built a prototype which supports this mechanism by(More)
In this paper, we propose a new method for addressing post-purchase recommendations for a dynamic marketplace. The proposed method uses the transactional data as the primary data source to mine co-purchase relationships. The item listings from the transactional data are mapped to their static `cluster' representation and a cluster-cluster directed graph is(More)
Query auto-completion (QAC) is an important feature of a search system that helps users reach their target queries faster. Personalization is a powerful technique that improves the relevance of QAC to the current query. This paper proposes a novel framework, EXOS, to augment the native query by important tokens in the user's search contexts to provide(More)
  • 1