کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10151083 1666105 2018 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Finding and analysing good neighbourhoods to improve collaborative filtering
ترجمه فارسی عنوان
پیدا کردن و تجزیه و تحلیل محله های خوب برای بهبود فیلتر همکاری
کلمات کلیدی
فیلتر کردن همگانی، سیستم پیشنهاد دهنده مبتنی بر محله، تجزیه و تحلیل محله،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
The research community has historically addressed the collaborative filtering task in several fashions. Although model-based approaches such as matrix factorisation attract substantial research efforts, neighbourhood-based recommender systems are effective and interpretable techniques. The performance of neighbour-based methods is strongly tied to the clustering strategies. In this paper, we show that there is room for improvement in this type of recommenders. For showing that, we build an oracle which yields approximately optimal neighbourhoods. We obtain ground truth neighbourhoods using the oracle and perform an analytical study of those to characterise them. As a result of our analysis, we propose to change the user profile size normalisation that cosine similarity employs in order to improve the neighbourhoods computed with k-NN algorithm. Additionally, we present a more appropriate oracle for current grouping strategies which leads us to include the IDF effect on the cosine formulation. An extensive experimentation on four datasets shows an increase in ranking accuracy, diversity and novelty using these cosine variants. This work shed light on the benefits of this type of analysis and paves the way for future research in the characterisation of good neighbourhoods for collaborative filtering.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 159, 1 November 2018, Pages 193-202
نویسندگان
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