activity
20172022
most citedTable2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval

95 citations · 343 across the 10 of their papers we have counts for

collaborators

16 papers

cs.IR202218 cited

Analyzing and Simulating User Utterance Reformulation in Conversational Recommender Systems

Shuo Zhang, Mu-Chun Wang, Krisztian Balog

User simulation has been a cost-effective technique for evaluating conversational recommender systems. However, building a human-like simulator is still an open challenge. In this…

cs.IR202235 cited

StruBERT: Structure-aware BERT for Table Search and Matching

Mohamed Trabelsi, Zhiyu Chen, Shuo Zhang +2

A large amount of information is stored in data tables. Users can search for data tables using a keyword-based query. A table is composed primarily of data values that are organize…

cs.IR202016 cited

IAI MovieBot: A Conversational Movie Recommender System

Javeria Habib, Shuo Zhang, Krisztian Balog

Conversational recommender systems support users in accomplishing recommendation-related goals via multi-turn conversations. To better model dynamically changing user preferences a…

cs.IR20205 cited

Generating Categories for Sets of Entities

Shuo Zhang, Krisztian Balog, Jamie Callan

Category systems are central components of knowledge bases, as they provide a hierarchical grouping of semantically related concepts and entities. They are a unique and valuable re…

cs.IR202084 cited

Evaluating Conversational Recommender Systems via User Simulation

Shuo Zhang, Krisztian Balog

Conversational information access is an emerging research area. Currently, human evaluation is used for end-to-end system evaluation, which is both very time and resource intensive…

cs.IR202014 cited

Summarizing and Exploring Tabular Data in Conversational Search

Shuo Zhang, Zhuyun Dai, Krisztian Balog +1

Tabular data provide answers to a significant portion of search queries. However, reciting an entire result table is impractical in conversational search systems. We propose to gen…