منابع مشابه
Item-properties may influence item-item associations in serial recall.
Attributes of words, such as frequency and imageability, can influence memory for order. In serial recall, Hulme, Stuart, Brown, and Morin (Journal of Memory and Language, 49(4), 500-518, 2003) found that high-frequency words were recalled worse, and low-frequency words better, when embedded in alternating lists than pure lists. This is predicted by associative chaining, wherein each recalled l...
متن کاملPsychometric Properties of 20-Item and 10-Item Persian Versions of Drug Abuse Screening Test
Introduction: Substance use disorder is one of the most critical social problems in Iran. For this disorder, weneed a proper assessment tool based on our indigenous culture. Objective: This study assesses the factor structure and psychometric properties of 10-item and 20-item Persian versions of Drug Abuse Screening Tests (DAST-10 and DAST-20). Materials and Methods: In this cross-sectional s...
متن کاملRegret Guarantees for Item-Item Collaborative Filtering
There is much empirical evidence that item-item collaborative filtering works well in practice. Motivated to understand this, we provide a framework to design and analyze various recommendation algorithms. The setup amounts to online binary matrix completion, where at each time a random user requests a recommendation and the algorithm chooses an entry to reveal in the user’s row. The goal is to...
متن کاملAmazon.com Recommendations: Item-to-Item Collaborative Filtering
R ecommendation algorithms are best known for their use on e-commerce Web sites,1 where they use input about a customer’s interests to generate a list of recommended items. Many applications use only the items that customers purchase and explicitly rate to represent their interests, but they can also use other attributes, including items viewed, demographic data, subject interests, and favorite...
متن کاملItem-Item Music Recommendations With Side Information
Online music services have tens of millions of tracks. The content itself is broad and covers various musical genres as well as non-musical audio content such as radio plays and podcasts. The sheer scale and diversity of content makes it difficult for a user to find relevant tracks. Relevant recommendations are therefore crucial for a good user experience. Here we present a method to compute tr...
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ژورنال
عنوان ژورنال: American Journal of Obstetrics and Gynecology
سال: 1921
ISSN: 0002-9378
DOI: 10.1016/s0002-9378(15)32468-6