17 citations · 20 across the 4 of their papers we have counts for
6 papers
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…
Offline and Online Satisfaction Prediction in Open-Domain Conversational Systems
Jason Ingyu Choi, Ali Ahmadvand, Eugene Agichtein
Predicting user satisfaction in conversational systems has become critical, as spoken conversational assistants operate in increasingly complex domains. Online satisfaction predict…
Contextual Dialogue Act Classification for Open-Domain Conversational Agents
Ali Ahmadvand, Jason Ingyu Choi, Eugene Agichtein
Classifying the general intent of the user utterance in a conversation, also known as Dialogue Act (DA), e.g., open-ended question, statement of opinion, or request for an opinion,…
ConCET: Entity-Aware Topic Classification for Open-Domain Conversational Agents
Ali Ahmadvand, Harshita Sahijwani, Jason Ingyu Choi +1
Identifying the topic (domain) of each user's utterance in open-domain conversational systems is a crucial step for all subsequent language understanding and response tasks. In par…
User Intent Inference for Web Search and Conversational Agents
Ali Ahmadvand
User intent understanding is a crucial step in designing both conversational agents and search engines. Detecting or inferring user intent is challenging, since the user utterances…