Towards Memorable Information Retrieval

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Abstract

Information overload is a problem many of us can relate to nowadays. The deluge of user generated content on the Internet, and the easy accessibility to a vast amount of data compounds the problem of remembering and retaining information that is consumed. To make information consumed more memorable, strategies such as note-taking have been found to be effective by augmenting human memory under specific conditions. This is based on the rationale that humans tend to recall information better if they have produced the information themselves. Previous works in online education have shown that conversational systems can improve learning effects. Although memorization is an important part of learning, the effect of conversation on human memorability remains unexplored. We aim to address this knowledge gap through an experimental study, by investigating human memorability in a classical information retrieval setup. We explore the impact of note-taking affordances and conversational interfaces on the memorability of information consumed by users. Our results show that traditional web search and note-taking have positive effects on knowledge gain, while the search engine with a conversational interface has the potential to augment long-term memorability. This work highlights the benefits of using note-taking and conversational interfaces to aid human memorability. Our findings have important implications on building information retrieval systems that cater to optimizing memorability of information consumed.

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Qiu, S., Gadiraju, U., & Bozzon, A. (2020). Towards Memorable Information Retrieval. In ICTIR 2020 - Proceedings of the 2020 ACM SIGIR International Conference on Theory of Information Retrieval (pp. 69–76). Association for Computing Machinery. https://doi.org/10.1145/3409256.3409830

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