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Zhu, P. (author), Câmara, Arthur (author), Roy, N. (author), Maxwell, D.M. (author), Hauff, C. (author)
Actively engaging learners with learning materials has been shown to be very important in the Search as Learning (SAL) setting. One active reading strategy relies on asking so-called adjunct questions, i.e., manually curated questions geared towards essential concepts of the target material. However, manual question creation is impractical...
conference paper 2024
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Roy, N. (author), Balayn, A.M.A. (author), Maxwell, D.M. (author), Hauff, C. (author)
The creation of relevance assessments by human assessors (often nowadays crowdworkers) is a vital step when building IR test collections. Prior works have investigated assessor quality & behaviour, and tooling to support assessors in their task. We have few insights though into the impact of a document's presentation modality on assessor...
conference paper 2023
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Azzopardi, Leif (author), Maxwell, D.M. (author), Halvey, Martin (author), Hauff, C. (author)
Advertisements, sponsored links, clickbait, in-house recommendations and similar elements pervasively shroud featured content. Such elements vie for people's attention, potentially distracting people from their task at hand. The effects of such "distractors"is likely to increase people's cognitive workload and reduce their performance as they...
conference paper 2023
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Penha, G. (author), Hauff, C. (author)
A number of learned sparse and dense retrieval approaches have recently been proposed and proven effective in tasks such as passage retrieval and document retrieval. In this paper we analyze with a replicability study if the lessons learned generalize to the retrieval of responses for dialogues, an important task for the increasingly popular...
conference paper 2023
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Zhu, P. (author), Wang, Z. (author), Yang, J. (author), Hauff, C. (author), Anand, A. (author)
Quality control is essential for creating extractive question answering (EQA) datasets via crowdsourcing. Aggregation across answers, i.e. word spans within passages annotated, by different crowd workers is one major focus for ensuring its quality. However, crowd workers cannot reach a consensus on a considerable portion of questions. We...
conference paper 2022
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Zhu, P. (author), Hauff, C. (author)
Question generation (QG) approaches based on large neural models require (i) large-scale and (ii) high-quality training data. These two requirements pose difficulties for specific application domains where training data is expensive and difficult to obtain. The trained QG models' effectiveness can degrade significantly when they are applied...
conference paper 2022
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Salimzadeh, S. (author), Gadiraju, Ujwal (author), Hauff, C. (author), van Deursen, A. (author)
Natural Language Interfaces to Databases (NLIDB), also known as Text-to-SQL models, enable users with different levels of knowledge in Structured Query Language (SQL) to access relational databases without any programming effort. By translating natural languages into SQL query, not only do NLIDBs minimize the burden of memorizing the schema...
conference paper 2022
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Roy, N. (author), Maxwell, D.M. (author), Hauff, C. (author)
The Search Engine Results Page (SERP) has evolved significantly over the last two decades, moving away from the simple ten blue links paradigm to considerably more complex presentations that contain results from multiple verticals and granularities of textual information. Prior works have investigated how user interactions on the SERP are...
conference paper 2022
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Câmara, Arthur (author), Maxwell, D.M. (author), Hauff, C. (author)
Complex search tasks—such as those from the Search as Learning (SAL) domain—often result in users developing an information need composed of several aspects. However, current models of searcher behaviour assume that individuals have an atomic need, regardless of the task. While these models generally work well for simpler informational needs,...
conference paper 2022
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Penha, G. (author), Câmara, Arthur (author), Hauff, C. (author)
Heavily pre-trained transformers for language modeling, such as BERT, have shown to be remarkably effective for Information Retrieval (IR) tasks, typically applied to re-rank the results of a first-stage retrieval model. IR benchmarks evaluate the effectiveness of retrieval pipelines based on the premise that a single query is used to...
conference paper 2022
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Roy, N. (author), Valle Torre, M. (author), Gadiraju, Ujwal (author), Maxwell, D.M. (author), Hauff, C. (author)
Active reading strategies - -such as content annotations (through the use of highlighting and note-taking, for example) - -have been shown to yield improvements to a learner's knowledge and understanding of the topic being explored. This has been especially notable in long and complex learning endeavours. With web search engines nowadays used...
conference paper 2021
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Roy, N. (author), Câmara, Arthur (author), Maxwell, D.M. (author), Hauff, C. (author)
Models developed to simulate user interactions with search interfaces typically do not consider the visual layout and presentation of a Search Engine Results Page (SERP). In particular, the position and size of interfacewidgets ---such as entity cards and query suggestions---are usually considered a negligible constant. In contrast, in this work...
conference paper 2021
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Roy, N. (author), Valle Torre, M. (author), Gadiraju, Ujwal (author), Maxwell, D.M. (author), Hauff, C. (author)
Prior work in education research has shown that various active reading strategies, notably highlighting and note-taking, benefit learning outcomes. Most of these findings are based on observational studies where learners learn from a single document. In a Search as Learning (SAL) context where learners have to iteratively scan and explore a...
conference paper 2021
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Salimzadeh, S. (author), Maxwell, D.M. (author), Hauff, C. (author)
Entity cards are a common occurrence in today's web Search Engine Results Pages (SERPs). SERPs provide information on a complex information object in a structured manner. Typically, they combine data from several search verticals. They have been shown to: (i) increase users' engagement with the SERP; and (ii) improve decision making for certain...
conference paper 2021
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Câmara, Arthur (author), Roy, N. (author), Maxwell, D.M. (author), Hauff, C. (author)
Web search engines are today considered to be the primary tool to assist and empower learners in finding information relevant to their learning goals- be it learning something new, improving their existing skills, or just fulfilling a curiosity. While several approaches for improving search engines for the learning scenario have been proposed...
conference paper 2021
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Maxwell, D.M. (author), Hauff, C. (author)
Logging user interactions is fundamental to capturing and subsequently analysing user behaviours in the context of web-based Interactive Information Retrieval (IIR). However, logging is often implemented within experimental apparatus in a piecemeal fashion, leading to incomplete or noisy data. To address these issues, we present the LogUI...
conference paper 2021
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Penha, G. (author), Hauff, C. (author)
The area of conversational search has gained significant traction in the IR research community, motivated by the widespread use of personal assistants. An often researched task in this setting is conversation response ranking, that is, to retrieve the best response for a given ongoing conversation from a corpus of historic conversations....
conference paper 2020
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Clancy, Ryan (author), Ferro, Nicola (author), Hauff, C. (author), Lin, Jimmy (author), Sakai, Tetsuya (author), Wu, Ze Zhong (author)
conference paper 2019
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Bountouridis, D. (author), Harambam, Jaron (author), Makhortykh, Mykola (author), Marrero Llinares, M. (author), Tintarev, N. (author), Hauff, C. (author)
The growing volume of digital data stimulates the adoption of recommender systems in different socioeconomic domains, including news industries. While news recommenders help consumers deal with information overload and increase their engagement, their use also raises an increasing number of societal concerns, such as “Matthew effects”, “filter...
conference paper 2019
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Hauff, C. (author)
The Lemur Project was set up in 2000 by the Center for Intelligent Information Retrieval at UMass Amherst. It is one of the longest lasting open-source projects in the information retrieval (IR) research community. Among the released tools is Indri, a popular search engine that was designed for language-modeling based approaches to IR. For...
conference paper 2019
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