Svitlana Vakulenko explains how we have recently used process mining techniques to understand the structure of interaction processes, which will in turn help us to improve information-seeking dialogue systems. We extract a new model of information-seeking dialogues, QRFA, for Query, Request, Feedback, Answer. The QRFA model better reflects conversation flows observed in real information-seeking conversations…
Investeer in kennisbasis AI of word een toeschouwer
In een opiniestuk voor NRC Handelsblad en NRC Next beargumenteer ik dat artificiële intelligentie ons leven hoe dan ook zal veranderen en dat Nederland voor de keuze staat om vol mee te doen in de ontwikkeling van AI en het spel mee te bepalen, of om de bank te blijven zitten. Wie niet actief meedoet,…
Learning to answer questions by taking broader contexts into account
Mostafa Dehghani has posted an explanation of our recent work on TraCRNet (“tracker net”) to learn how to answer questions from multiple, possible long documents. TraCRNet uses the universal transformer and is able to go beyond understanding a set of input documents separately and combine their information in multiple steps. TraCRNet is highly parallellizable and…
FACTS-IR Workshop @ SIGIR 2019
SIGIR 2019 will host a workshop to explore challenges in responsible information retrieval system development and deployment. The focus will be on determining actionable research agendas on five key dimensions of responsible information retrieval: fairness, accountability, confidentiality, transparency, and safety. Rather than just a mini-conference, this workshop will be an event during which participants will…
How to optimize ranking systems by directly interacting with users
Harrie Oosterhuis has written an accessible summary of our recent work on pairwise differentiable gradient descent (PDGD), an online learning to rank method that he published at CIKM 2018, with a follow-up paper to come at ECIR 2019 in April. With the introduction of the PDGD algorithm, ranking systems can now be optimized from user…
WWW 2019 paper on evaluation metrics for web image search online
Grid-based Evaluation Metrics for Web Image Search by Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Maarten de Rijke, Yunqiu Shao, Zixin Ye, Min Zhang, and Shaoping Ma is online now at this location. Compared to general web search engines, web image search engines display results in a different way. In web image search, results are typically placed…
WWW 2019 paper on outfit recommendation online
Improving Outfit Recommendation with Co-supervision of Fashion Generation by Yujie Lin, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Jun Ma, and Maarten de Rijke is now available at this location. The task of fashion recommendation includes two main challenges:visual understanding and visual matching. Visual understanding aims to extract effective visual features. Visual matching aims to model a human notion…
WWW 2019 paper on diversity of dialogue response generation online
Improving Neural Response Diversity with Frequency-Aware Cross-Entropy Loss by Shaojie Jiang, Pengjie Ren, Christof Monz, and Maarten de Rijke is online now at this location. Sequence-to-Sequence (Seq2Seq) models have achieved encouraging performance on the dialogue response generation task. However, existing Seq2Seq-based response generation methods suffer from a low-diversity problem: they frequently generate generic responses, which make the…
WWW 2019 paper on visual learning to rank online
ViTOR: Learning to Rank Webpages Based on Visual Features by Bram van den Akker, Ilya Markov, and Maarten de Rijke is available online now at this location. The visual appearance of a webpage carries valuable information about the page’s quality and can be used to improve the performance of learning to rank (LTR). We introduce the Visual…
ECIR 2019 paper on information-seeking dialogues online
QRFA: A data-driven model of information-seeking dialogues by Svitlana Vakulenko, Kate Revoredo, Claudio Di Ciccio, and Maarten de Rijke is available online now at this location. Understanding the structure of interaction processes helps us to improve information-seeking dialogue systems. Analyzing an interaction process boils down to discovering patterns in sequences of alternating utterances exchanged between a…