activity
20122023
most citedOpenTag: Open Attribute Value Extraction from Product Profiles [Deep Learning, Active Learning, Named Entity Recognition]

157 citations · 618 across the 30 of their papers we have counts for

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6 papers · 1 filter

cs.AI2017★ 106 cited

People on Media: Jointly Identifying Credible News and Trustworthy Citizen Journalists in Online Communities

Subhabrata Mukherjee, Gerhard Weikum

Media seems to have become more partisan, often providing a biased coverage of news catering to the interest of specific groups. It is therefore essential to identify credible info…

cs.AI2017★ 2 cited

Credible Review Detection with Limited Information using Consistency Analysis

Subhabrata Mukherjee, Sourav Dutta, Gerhard Weikum

Online reviews provide viewpoints on the strengths and shortcomings of products/services, influencing potential customers' purchasing decisions. However, the proliferation of non-c…

cs.AI2017★ 14 cited

People on Drugs: Credibility of User Statements in Health Communities

Subhabrata Mukherjee, Gerhard Weikum, Cristian Danescu-Niculescu-Mizil

Online health communities are a valuable source of information for patients and physicians. However, such user-generated resources are often plagued by inaccuracies and misinformat…

cs.AI2017★ 20 cited

Item Recommendation with Evolving User Preferences and Experience

Subhabrata Mukherjee, Hemank Lamba, Gerhard Weikum

Current recommender systems exploit user and item similarities by collaborative filtering. Some advanced methods also consider the temporal evolution of item ratings as a global ba…

cs.AI2017

Exploring Latent Semantic Factors to Find Useful Product Reviews

Subhabrata Mukherjee, Kashyap Popat, Gerhard Weikum

Online reviews provided by consumers are a valuable asset for e-Commerce platforms, influencing potential consumers in making purchasing decisions. However, these reviews are of va…

cs.AI2017★ 7 cited

Item Recommendation with Continuous Experience Evolution of Users using Brownian Motion

Subhabrata Mukherjee, Stephan Guennemann, Gerhard Weikum

Online review communities are dynamic as users join and leave, adopt new vocabulary, and adapt to evolving trends. Recent work has shown that recommender systems benefit from expli…