EXTRA: Explanation Ranking Datasets for Explainable Recommendation

Lei Li, Yongfeng Zhang, Li Chen

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

Recently, research on explainable recommender systems has drawn much attention from both academia and industry, resulting in a variety of explainable models. As a consequence, their evaluation approaches vary from model to model, which makes it quite difficult to compare the explainability of different models. To achieve a standard way of evaluating recommendation explanations, we provide three benchmark datasets for EXplanaTion RAnking (denoted as EXTRA), on which explainability can be measured by ranking-oriented metrics. Constructing such datasets, however, poses great challenges. First, user-item-explanation triplet interactions are rare in existing recommender systems, so how to find alternatives becomes a challenge. Our solution is to identify nearly identical sentences from user reviews. This idea then leads to the second challenge, i.e., how to efficiently categorize the sentences in a dataset into different groups, since it has quadratic runtime complexity to estimate the similarity between any two sentences. To mitigate this issue, we provide a more efficient method based on Locality Sensitive Hashing (LSH) that can detect near-duplicates in sub-linear time for a given query. Moreover, we make our code publicly available to allow researchers in the community to create their own datasets.
Original languageEnglish
Title of host publicationSIGIR '21- Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery (ACM)
Pages2463-2469
Number of pages7
ISBN (Print)9781450380379
Publication statusPublished - Jul 2021
Event44th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021 - Virtual, Montreal, Canada
Duration: 11 Jul 202115 Jul 2021
https://sigir.org/sigir2021/

Conference

Conference44th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021
Country/TerritoryCanada
CityMontreal
Period11/07/2115/07/21
Internet address

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