18 citations · 97 across the 27 of their papers we have counts for
14 papers · 1 filter
Enhancing Healthcare Search Intent Recognition with Query Representation Learning and Session Context
Chen Lin, Harshita Jagdish Sahijwani, Madhav Sigdel +4
Classifying the intent behind healthcare search queries is crucial for improving the delivery of online healthcare information. The intricate nature of medical search queries, coup…
GenQREnsemble: Zero-Shot LLM Ensemble Prompting for Generative Query Reformulation
Kaustubh Dhole, Eugene Agichtein
Query Reformulation(QR) is a set of techniques used to transform a user's original search query to a text that better aligns with the user's intent and improves their search experi…
DUQGen: Effective Unsupervised Domain Adaptation of Neural Rankers by Diversifying Synthetic Query Generation
Ramraj Chandradevan, Kaustubh D. Dhole, Eugene Agichtein
State-of-the-art neural rankers pre-trained on large task-specific training data such as MS-MARCO, have been shown to exhibit strong performance on various ranking tasks without do…
QueryExplorer: An Interactive Query Generation Assistant for Search and Exploration
Kaustubh D. Dhole, Shivam Bajaj, Ramraj Chandradevan +1
Formulating effective search queries remains a challenging task, particularly when users lack expertise in a specific domain or are not proficient in the language of the content. P…
Contextual Response Interpretation for Automated Structured Interviews: A Case Study in Market Research
Harshita Sahijwani, Kaustubh Dhole, Ankur Purwar +2
Structured interviews are used in many settings, importantly in market research on topics such as brand perception, customer habits, or preferences, which are critical to product d…
Making Large Language Models Interactive: A Pioneer Study on Supporting Complex Information-Seeking Tasks with Implicit Constraints
Ali Ahmadvand, Negar Arabzadeh, Julia Kiseleva +7
Current interactive systems with natural language interfaces lack the ability to understand a complex information-seeking request which expresses several implicit constraints at on…
RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search
Jianghong Zhou, Eugene Agichtein
To support complex search tasks, where the initial information requirements are complex or may change during the search, a search engine must adapt the information delivery as the…
Diversifying Multi-aspect Search Results Using Simpson's Diversity Index
Jianghong Zhou, Eugene Agichtein, Surya Kallumadi
In search and recommendation, diversifying the multi-aspect search results could help with reducing redundancy, and promoting results that might not be shown otherwise. Many previo…
De-Biased Modelling of Search Click Behavior with Reinforcement Learning
Jianghong Zhou, Sayyed M. Zahiri, Simon Hughes +3
Users' clicks on Web search results are one of the key signals for evaluating and improving web search quality and have been widely used as part of current state-of-the-art Learnin…
DeepCAT: Deep Category Representation for Query Understanding in E-commerce Search
Ali Ahmadvand, Surya Kallumadi, Faizan Javed +1
Mapping a search query to a set of relevant categories in the product taxonomy is a significant challenge in e-commerce search for two reasons: 1) Training data exhibits severe cla…
APRF-Net: Attentive Pseudo-Relevance Feedback Network for Query Categorization
Ali Ahmadvand, Sayyed M. Zahiri, Simon Hughes +3
Query categorization is an essential part of query intent understanding in e-commerce search. A common query categorization task is to select the relevant fine-grained product cate…
Semantic Product Search for Matching Structured Product Catalogs in E-Commerce
Jason Ingyu Choi, Surya Kallumadi, Bhaskar Mitra +2
Retrieving all semantically relevant products from the product catalog is an important problem in E-commerce. Compared to web documents, product catalogs are more structured and sp…
Would You Like to Hear the News? Investigating Voice-BasedSuggestions for Conversational News Recommendation
Harshita Sahijwani, Jason Ingyu Choi, Eugene Agichtein
One of the key benefits of voice-based personal assistants is the potential to proactively recommend relevant and interesting information. One of the most valuable sources of such…
JointMap: Joint Query Intent Understanding For Modeling Intent Hierarchies in E-commerce Search
Ali Ahmadvand, Surya Kallumadi, Faizan Javed +1
An accurate understanding of a user's query intent can help improve the performance of downstream tasks such as query scoping and ranking. In the e-commerce domain, recent work in…