Top-N news recommendations in digital newspapers

Cleger-Tamayo, Sergio; Fernández‐Luna, Juan M.; Huete, Juan F.

doi:10.1016/j.knosys.2011.11.017

Cited by 42 publications

(27 citation statements)

References 29 publications

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“…Giving rating to something that user favors is one method to gain user interest. Some researches develop this method to get better personalization in movie website [1] or in digital newspaper [11]. In e-commerce, the consumer gives a rating on the product after purchasing the goods.…”

Section: Consumer Interest In the E-commerce Productsmentioning

confidence: 99%

The Measurement of Consumer Interest and Prediction of Product Selection in E-commerce Using Eye Tracking Method

Sari¹,

Nugroho²,

Santosa³

et al. 2018

IJIES

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Abstract:Consumer interest in products is recognized after the consumer buys products and provides a rating on it. Development of technology can get consumer interest in products through eyes. The technology used is eye tracking using eye tracker tool. Attraction Measurement is used to measure consumer interest. This method can be used to recognize attractive product display and measure consumers preference and consumers emotions in products. In this study, an experiment was conducted to determine consumer interest in the selva-house website with three products of hijabs. The study found that fixation duration can be used to recognize consumer interest in products. Another measurement is to determine whether consumers are willing to buy the products. The experiment results that consumer interest measurement and prediction of product selection measurement indicate that the second product is preferred by the consumers.This research shows that consumer interest model and prediction of product selection model, and the result of prediction measurement have a contribution to product recommendations for further research.

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Section: Consumer Interest In the E-commerce Productsmentioning

confidence: 99%

The Measurement of Consumer Interest and Prediction of Product Selection in E-commerce Using Eye Tracking Method

Sari¹,

Nugroho²,

Santosa³

et al. 2018

IJIES

View full text Add to dashboard Cite

show abstract

“…To measure user interest, some characteristics of user behavior have been examined, for example product rating [12,13], purchasing records [14], page discussed sequence [15], page detention time [16][17][18][19], page browsing frequency [20,21], and contextual information [22]. More specifically, White, et al [22] conducted a study on the effectiveness of five different types of contextual information sources to perform modeling of user interest.…”

Section: Related Workmentioning

confidence: 99%

Research Methodology for Analysis of E-Commerce User Activity Based on User Interest using Web Usage Mining

2018

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Abstract. Visitor interaction with e-commerce websites generates large amounts of clickstream data stored in web access logs. From a business standpoint, clickstream data can be used as a means of finding information on user interest. In this paper, the authors propose a method to find user interest in products offered on e-commerce websites based on web usage mining of clickstream data. In this study, user interest was investigated using the PIE approach coupled with clustering and classification techniques. The experimental results showed that the method is able to assist in analyzing visitor behavior and user interest in ecommerce products by identifying those products that prompt visitor interest.

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“…RS is uses by many areas in web such as movies [5], music [6], news [7], tourism [8], social networks [9] and scientific papers [10]. The main approaches of the recommenders includes content based and collaborative filtering where the first one predicts the interests of the user based on the sole user's data whereas the later one predicts the interests of the user based on the similar user's data [11].…”

Section: Related Workmentioning

confidence: 99%

DBT Recommender: Improved Trustworthiness of Ratings through De-Biasing Tendency of Users

Mukkamula¹

2018

IJIES

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Recent advancements in business strategies marked the significance of e-commerce in marketing any service of the organization. Moreover, users are quiet dependent on the average ratings of the products showcased in the marketing interface in turn these average ratings made remarkable impact on sales phenomena of the product. The average rating of a product is the aggregation of individual users ratings biased with the tendency of the user towards publishing the opinion. The optimistic user tends to give a slight high rating than a neutral judgement and vice versa with a pessimistic user. However, these biased ratings produce an aggregate value that is degraded with its trustworthiness. This paper proposed a novel approach named DBT (De-biased Tendency) Recommender to analyze the bias in product rating which recalculates the average ratings of the products by making user tendencies as part of the process. The solution implemented on a big data environment on demand of high computation complexity involved in the process. Experimental results had shown a significant improvement in the trustworthiness of the product ratings with the proposed approach.

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Top-N news recommendations in digital newspapers

Cited by 42 publications

References 29 publications

The Measurement of Consumer Interest and Prediction of Product Selection in E-commerce Using Eye Tracking Method

The Measurement of Consumer Interest and Prediction of Product Selection in E-commerce Using Eye Tracking Method

Research Methodology for Analysis of E-Commerce User Activity Based on User Interest using Web Usage Mining

DBT Recommender: Improved Trustworthiness of Ratings through De-Biasing Tendency of Users

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