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Journals / Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik / 2013 / Cilt: 14 - Sayı: 1

İKİLİ BENZERLİK METRİKLERİNİN ÜST-N ÖNERİLERİNE ETKİSİ

EFFECTS OF BINARY SIMILARITY MEASURES ON TOP-N RECOMMENDATIONS

Edip ŞENYÜREK
Hüseyin POLAT
Pages
55–65
Publication Date
2022-10-11
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Similarity measures used to find out the most similar entities might affect theoverall performance of top-N predictions.

📌 3 Key Takeaways

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Objective & Hypothesis:Shopping over the Internet through several e-commerce sites is receiving increasing attention.Customers want to purchase those products that they might like without wasting time and/or money.To help their customers, many online companies provide top-N recommendations by means of recommender systems.
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Key Findings & Data:Similarity measures used to find out the most similar entities might affect theoverall performance of top-N predictions.
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Conclusion & Impact:We analyze our empirical results and providesome suggestions.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Shopping over the Internet through several e-commerce sites is receiving increasing attention.Customers want to purchase those products that they might like without wasting time and/or money.To help their customers, many online companies provide top-N recommendations by means of recommender systems. Similarity measures used to find out the most similar entities might affect theoverall performance of top-N predictions. Although there are various binary ratings-based similaritymetrics, their effects on accuracy and online efficiency of top-N recommendations have not beendeeply studied. In this study, we investigate seven well-known binary ratings-based similarity metrics in terms ofboth preciseness and efficiency while providing top-N recommendations. To compare them with re- spect to accuracy and competence, we perform several experiments based on two well-known real datasets. We modify top-N recommendation algorithm in such a way so that the most similar users dataare involved in recommendation process. We also study how varying controlling parameters affectoverall performance with different similarity metrics. We analyze our empirical results and providesome suggestions.

Özet

İnternet üzerinden sanal firmalar aracılığıyla alışveriş yapmak artan ilgi görmektedir. Müşterilerbeğenebilecekleri ürünleri zaman ve/veya paralarını boşa harcamadan satın almak isterler. Müşteri- lerine bu süreçte yardımcı olmak için birçok sanal şirket öneri sistemlerinden yararlanıp müşterilerineen-iyi-N önerileri sunmaktadır. En benzer varlıkları belirlemede kullanılan benzerlik ölçütleri en-iyi-N önerileri hizmetinin genel performansını etkileyebilir. İkili değerler üzerinde işlem yapan birçok ben- zerlik ölçütü bulunmasına rağmen bunların en-iyi-N önerilerinin doğruluğu ve çevrimiçi performansıüzerindeki etkisi detaylı biçimde çalışılmamıştır.Bu çalışmada iyi bilinen yedi adet ikili oy-tabanlı benzerlik ölçütü en-iyi-N önerileri için hemdoğruluk hem de çevrimiçi performans kriterleri bakımından irdelendi. Bu ölçütleri doğruluk veverimlilik açısından karşılaştırabilmek için iyi bilinen iki gerçek veri seti üzerinde birçok deneyler yapıldı. Ayrıca en-iyi-N öneri algoritması en benzer kullanıcıların verisi öneri üretilirken kullanılacakşekilde değiştirildi. Değişen kontrol parametrelerinin performansa olan etkisi araştırıldı. Deneyselsonuçlar doğruluk ve performans açısından analiz edilerek bazı öneriler sunuldu.

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Cite This Article

ŞENYÜREK, E., POLAT, H. (2022). İKİLİ BENZERLİK METRİKLERİNİN ÜST-N ÖNERİLERİNE ETKİSİ. Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik, Cilt: 14 - Sayı: 1, 55–65. https://ajindex.com/articles/438390

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