Web mining based framework for solving usual problems in recommender systems. A case study for movies׳ recommendation

Moreno, María N.; Segrera, Saddys; López, Vivian F.; Muñoz, María Dolores; Sánchez, Ángel Luis

doi:10.1016/j.neucom.2014.10.097

Cited by 68 publications

(31 citation statements)

References 29 publications

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“…An automatic recommendation scheme based on collaborative filtering infers the preferred TV programs in two stages [4]. At the first stage, a candidate set of programs is generated on the grounds of the users' watching history [5]. At the second stage, the candidate TV programs are ranked to eliminate the recommendation redundancy stipulated by items similarity [4].…”

Section: Discussionmentioning

confidence: 99%

Television Rating Control in the Multichannel Environment Using Trend Fuzzy Knowledge Bases and Monitoring Results

Азаров

Krupelnitsky

Rakytyanska

2018

Data

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The purpose of this study is to control the ratio of programs of different genres whenforming the broadcast grid in order to increase and maintain the rating of a channel. In themultichannel environment, television rating controls consist of selecting content, the ratings ofwhich are completely restored after advertising. The hybrid approach to rule set refinement basedon fuzzy relational calculus simplifies the process of expert recommendation systems construction.By analogy with the problem of the inverted pendulum control, the managerial actions aim to retainthe balance between the fuzzy demand and supply. The increase or decrease trends of the demandand supply are described by primary fuzzy relations. The rule-based solutions of fuzzy relationalequations connect significance measures of the primary fuzzy terms. Program set refinement bysolving fuzzy relational equations allows avoiding procedures of content-based selective filtering.The solution set generation corresponds to the granulation of television time, where each solutionrepresents the time slot and the granulated rating of the content. In automated media planning,generation of the weekly TV program in the form of the granular solution provides the decrease oftime needed for the programming of the channel broadcast grid.

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Section: Discussionmentioning

confidence: 99%

Television Rating Control in the Multichannel Environment Using Trend Fuzzy Knowledge Bases and Monitoring Results

Азаров

Krupelnitsky

Rakytyanska

2018

Data

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“…The information can help, for instance, to find more books by an author they enjoy reading or have a movie title suggested to them based on interest in a topic. The information is honed and tailored over time to accurately detect and influence shopping habits (18). A similar feedback effect occurs with online information searches.…”

Section: Online Eating Disorder Datamentioning

confidence: 94%

Extreme Overvalued Beliefs

Rahman¹,

Mukherji²

2017

Preprint

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13Psychiatry needs operational definitions to appreciate differences seen in idiosyncratic, psychotic 14 thinking, and shared subcultural beliefs or ideologies. Carl Wernicke first described overvalued idea in 151906. The concept has been applied to describe it as a motive in mass shootings and terrorism. We review 16 the concept of overvalued idea and extreme overvalued belief as a basis for making the distinction 17 between delusions and non-delusions. 18Keywords: psychosis; delusion; over valued idea; terrorism; mass shootings; violence; forensic psychiatry 19 20 Psychiatry lacks operational definitions to differentiate idiosyncratic, psychotic thinking from 21 shared subcultural beliefs or ideologies. Rigidly-held non-delusional beliefs are an important 22 aspect behind the motive for many global and homegrown violent and terrorist attacks (1). The 23 fact that no particular sociodemographic information has been found to be associated with this 24 often aberrant behavior requires new strategies to be developed. Terrorism is a behavior that 25 Peer-reviewed version available at Behav. Sci. 2018, 8, 10; doi:10.3390/bs8010010 comes with enormous direct and indirect costs-lost lives, expensive counter-terrorism 26 programs, political division, loss of civil liberties, and psychological disorders (2). A literature 27 search on the topic of primary prevention of terrorism and mass shootings reveals strikingly little 28 scholarly academic work by psychiatrists. Media often erroneously report a terrorist attack as 29 based on delusional thinking, obsessional thinking or psychosis. This article reviews the concept 30 of over-valued idea, first defined by Carl Wernicke and later applied to terrorism as an important 31 area of psychopathology with important implications for both forensic evaluations and primary 32 prevention of terrorism and mass shootings. 33 Extreme Overvalued Beliefs 34There has previously been a lack of agreement as to what precisely constitutes an over-35 valued idea (3). Consensus regarding definitions is helpful to facilitate research and the 36 development of innovative strategies. In 2016, our group of forensic psychiatrists (Rahman, 37 Peer-reviewed version available at Behav. Sci. 2018, 8, 10; doi:10.3390/bs8010010 This definition expands on what was first described as Ueberwerthige Idee (overvalued 50 idea) by Carl Wernicke in Gundriss der Psychiatrie (1906) and later invoked by then 51 psychiatrist-in-chief Paul McHugh at Johns Hopkins in response to the 9/11 terrorist attacks (4). 52 FBI trained forensic behavioral specialist Matt Logan also discusses this concept in Lone Wolf 53 Killers: A Perspective on Overvalued Ideas (5). 54Wernicke is honored by having his name describe a type of aphasia, but his psychiatric 55 contributions have largely been neglected. Gundriss der Psychiatrie was recently translated 56 from German into English. In his classical description of overvalued idea, Wernicke stated that 57 "special conditions must prevail before such overemphasis takes o...

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“…Zhou et al in [20] recommend an incremental approach based on SVD that constantly computes the singular value decomposition of the original matrix unchanged each time to solve the sparsity problem and users' interests that are dynamic. Furthermore, other data mining techniques including clustering [21], classification [22], and association rules mining [23] have been used in recommender systems as solutions to the data sparsity.…”

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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Web mining based framework for solving usual problems in recommender systems. A case study for movies׳ recommendation

Cited by 68 publications

References 29 publications

Television Rating Control in the Multichannel Environment Using Trend Fuzzy Knowledge Bases and Monitoring Results

Television Rating Control in the Multichannel Environment Using Trend Fuzzy Knowledge Bases and Monitoring Results

Extreme Overvalued Beliefs

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

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