A new similarity measure for collaborative filtering based recommender systems

Gazdar, Achraf; Hidri, Lotfi

doi:10.1016/j.knosys.2019.105058

Cited by 113 publications

(58 citation statements)

References 12 publications

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“…Bag et al (2019) developed the relevant Jaccard similarity and Jaccard mean square distance similarity based on ratings data from the MovieLens dataset. Gazdar and Hidri (2020) proposed similarity using user ratings from MovieLens100K, MovieLens1M and Yahoo! Music data sets.…”

Section: Literature Reviewmentioning

confidence: 99%

Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns

Tang

Wang

Cui³

et al. 2021

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PurposeBecause of short life cycle and fluctuating greatly in total sales volumes (TSV), it is difficult to accumulate enough sales data and mine an attribute set reflecting the common needs of all consumers for a kind of experiential product with short life cycle (EPSLC). Methods for predicting TSV of long-life-cycle products may not be suitable for EPSLC. Furthermore, point prediction cannot obtain satisfactory prediction results because information available before production is inadequate. Thus, this paper aims at proposing and verifying a novel interval prediction method (IPM).Design/methodology/approachBecause interval prediction may satisfy requirements of preproduction investment decision-making, interval prediction was adopted, and then the prediction difficult was converted into a classification problem. The classification was designed by comparing similarities in attribute relationship patterns between a new EPSLC and existing product groups. The product introduction may be written or obtained before production and thus was designed as primary source information. IPM was verified by using data of crime movies released in China from 2013 to 2017.FindingsThe IPM is valid, which uses product introduction as input, classifies existing products into three groups with different TSV intervals, mines attribute relationship patterns using content and association analyses and compares similarities in attribute relationship patterns – to predict TSV interval of a new EPSLC before production.Originality/valueDifferent from other studies, the IPM uses product introduction to mine attribute relationship patterns and compares similarities in attribute relationship patterns to predict the interval values. It has a strong applicability in data content and structure and may realize rolling prediction.

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Section: Literature Reviewmentioning

confidence: 99%

Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns

Tang

Wang

Cui³

et al. 2021

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show abstract

“…However, Similarity measures are considered also essential tools to solve problems in a broad range of AI domains and applications, specially when semantic matters. For example semantic web and linked data [29], recommender systems [11], Natural Language Processing [22], Information Retrieval, Knowledge Engineering [3],and many others. There are several similarity measures that have been used in CBR systems, and some comparison studies and frameworks exist [18,14].…”

Section: Related Work About Similaritymentioning

confidence: 99%

User Evaluation to Measure the Perception of Similarity Measures in Artworks

Díaz-Agudo

Jiménez-Díaz

Jorro-Aragoneses

2021

Lecture Notes in Computer Science

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Similarity measures do not typically capture subjective elements of perception of similarity. Our research contributes an experimental methodology for validating and learning similarity computation algorithms against human perceptions of similarity in subjective domains like Art and emotions. In this paper, we explain the first experiment to check our hypotheses and methodology. We have obtained promising results that explain the differences between users profiles and their perception of similarity between artworks and how to combine local similarity functions to be able to compute similarity measures reflecting users' perception.

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“…Numerous similarity measures have been proposed to better capture the relationship patterns between users and items. The Pearson correlation coefficient (PCC), cosine similarity (COS), and the Jaccard index (JAC) are the most widely adopted similarity measures in the literature [12], [17], [26], [27], [28].…”

Section: B Similarity Measuresmentioning

confidence: 99%

Switching Hybrid Method Based on User Similarity and Global Statistics for Collaborative Filtering

Ortal

Edahiro

2020

IEEE Access

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Collaborative filtering (CF) is a technique used in recommender systems to provide meaningful suggestions based on known feedback obtained from like-minded users. The measure of similarity plays a critical role in the performance of neighborhood-based CF methods. However, conventional similarity measures suffer from limitations because they only consider the direction of the rating vectors. We propose a novel similarity measure that considers the semantic nuances of the ratings; in particular, it weights the contributions of ratings in proportion to the users' degree of indifference towards the items. Additionally, to address the sparsity problem that affects the performance of CF techniques, we propose a switching hybrid method that predicts user ratings based on either our custom similarity measure or through user and item biases. We evaluated the proposed method on six different datasets and compared it with other CF methods. The results show that the proposed recommender consistently outperforms those using conventional similarity measures when the sparsity of the dataset is high.

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A new similarity measure for collaborative filtering based recommender systems

Cited by 113 publications

References 12 publications

Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns

Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns

User Evaluation to Measure the Perception of Similarity Measures in Artworks

Switching Hybrid Method Based on User Similarity and Global Statistics for Collaborative Filtering

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