Design of Intelligent Film and Television Advertisements Recommendation System Based on Digital Media and Decision Tree

2021 ◽  
Author(s):  
Huawen Zhao ◽  
Yanhua Liu ◽  
Xiaohong Ling
Keyword(s):  
Decision Tree ◽  
Digital Media ◽  
Recommendation System ◽  
Film And Television ◽  
Television Advertisements

A comparative study to recognize fake ratings in recommendation system using classification techniques

2021 ◽  
pp. 1-8
Author(s):  
P. Shanmuga Sundari ◽  
M. Subaji
Keyword(s):  
Decision Tree ◽  
False Positive ◽  
Recommendation System ◽  
Target Item ◽  
User Profile ◽  
Method Performance ◽  
Classification Techniques ◽  
Attack Model ◽  
Unique Method ◽  
Decision Tree Method

The recommendation system is affected with attacks when the users are given liberty to rate the items based on their impression about the product or service. Some malicious user or other competitors’ try to inject fake rating to degrade the item’s graces that are mostly adored by several users. Attacks in the rating matrix are not executed just by a single profile. A group of users profile is injected into rating matrix to decrease the performance. It is highly complex to extract the fake ratings from the mixture of genuine profile as it resides the same pattern. Identifying the attacked profile and the target item of the fake rating is a challenging task in the big data environment. This paper proposes a unique method to identify the attacks in collaborating filtering method. The process of extracting fake rating is carried out in two phases. During the initial phase, doubtful user profile is identified from the rating matrix. In the following phase, the target item is analysed using push attack count to reduce the false positive rates from the doubtful user profile. The proposed model is evaluated with detection rate and false positive rates by considering the filler size and attacks size. The experiment was conducted with 6%, 8% and 10% filler sizes and with different attack sizes that ranges from 0%–100%. Various classification techniques such as decision tree, logistic regression, SVM and random forest methods are used to classify the fake ratings. From the results, it is witnessed that SVM model works better with random and bandwagon attack models at an average of 4% higher accuracy. Similarly the decision tree method performance better at an average of 3% on average attack model.

scholarly journals Symptoms to Disease Mapping and Doctor Recommendation System

2019 ◽  
Vol 9 (1) ◽  
pp. 1111-1119
Keyword(s):  
Decision Tree ◽  
Sentiment Analysis ◽  
Recommendation System ◽  
Disease Mapping ◽  
Uneven Distribution ◽  
Bayes Classifier ◽  
Doctor Who ◽  
Mining Technique ◽  
Review Mining ◽  
Doctor Recommendation

To find an appropriate doctor who is specialized to treat a certain disease while only symptoms are known is not easy job for the patients. In this paper, we describe a recommended framework to find the best doctors in accordance with patients' requirements. In the proposed system, first it considers only those doctors whose profile match with patients' requirements. Second, the best doctors will be recommended out of previously obtained doctors based on the parameter patients' feedback i.e., patients' review. Our proposal will suggest a doctor recommendation system that uses review mining technique, which can be used in those countries that have huge uneven distribution of medical resources. In our model we have used the decision tree for symptoms to disease mapping and Naive Bayes classifier for sentiment analysis which are connected to each other using a bridge of python logic and the required output is top doctors based on the users input

scholarly journals Implementation of a New Recommendation System Based on Decision Tree Using Implicit Relevance Feedback

2015 ◽  
Vol 10 (12) ◽  
pp. 1367-1374 ◽  
Author(s):  
Anıl Utku ◽  
◽  
Hacer Karacan ◽  
Oktay Yıldız ◽  
M. Ali Akcayol
Keyword(s):  
Decision Tree ◽  
Relevance Feedback ◽  
Recommendation System

Geographies of media and communication I

2016 ◽  
Vol 41 (3) ◽  
pp. 365-374 ◽  
Author(s):  
Paul C. Adams
Keyword(s):  
Digital Media ◽  
Progress Report ◽  
New Paradigm ◽  
Media Communication ◽  
Film And Television ◽  
Space And Time ◽  
Metaphysical Question ◽  
Media And Communication

Media and communication are attracting increasing amounts of attention from geographers but the work remains disorganized and lacks a unifying paradigm. This progress report suggests a new paradigm for geographical studies of media and communication and indicates how recent research fits under this umbrella. The report presents recent studies of literature, film and television, digital media, photography, comics, stamps and banknotes. The range of theoretical concerns in this body of work includes performance, agency, materiality, immateriality, networks, politics, emotions and affect. Collectively, these concerns point to communications not merely as transmissions through infrastructure, space and time, but rather as encounters between various human and nonhuman agents. The metaphysical question is exactly what such encounters do to participants – how agents are transformed by other agents’ communications. This leads to synthesis in a new paradigm for media/communication geography: the metaphysics of encounter.

scholarly journals Digital Media Platforms and the Use of TV Content: Binge Watching and Video-on-Demand in Germany

2016 ◽  
Vol 4 (3) ◽  
pp. 154-161 ◽  
Author(s):  
Lothar Mikos
Keyword(s):  
Digital Media ◽  
Video On Demand ◽  
Carrier Medium ◽  
Audience Studies ◽  
Film And Television ◽  
On Demand ◽  
Television Shows ◽  
The Future ◽  
Tv Shows ◽  
Television Market

The advancing digitalization and media convergence demands TV broadcasting companies to adjust their content to various platforms and distribution channels. The internet, as convergent carrier medium, is increasingly taking on a central role for additional media. Classical linear TV is still important, but for some audiences it has been developing from a primary medium to a secondary medium. Owing to the growing melding of classical-linear TV contents with online offerings (e.g. video-on-demand platforms or Web–TV), a great dynamic can be seen which has triggered numerous discussions about the future of TV for some time now. This article will summarize the results of two different audience studies. Film and television shows are meanwhile distributed online via Video-on-Demand platforms such as Netflix or Amazon Prime Video. The first audience study has dealt with the use of VoD-platforms in Germany investigating user rituals, user motivation to watch films and TV shows on these platforms, and the meaning of VoD in everyday life. Most of the participants in this study reported that they mainly watch TV drama series at Netflix or Amazon Prime. Therefore, the second audience study focused the online use of television drama series of individuals and couples elaborating the phenomenon of binge watching. In relating the audience practice to the new structures of the television market the article will shed light on the future of television.

The Entire Mystery: Paratexts and the Ever-Expanding Twin Peaks Universe

2018 ◽  
pp. 103-120
Author(s):  
Lindsay Hallam
Keyword(s):  
New York ◽  
Sexual Abuse ◽  
Digital Media ◽  
New York Times ◽  
Bestseller List ◽  
The New York Times ◽  
Film And Television ◽  
Twin Peaks ◽  
Initial Release ◽  
Effects Of Sexual Abuse

This chapter explains how the Twin Peaks universe has expanded beyond the mediums of film and television and into the areas of literature and digital media, which inspired countless works of fan-made artwork and fiction. It reviews a brief survey of some of the key paratexts that interlock with David Lynch's Twin Peaks: Fire Walk With Me, which opens up new facets and insights into the film's narrative. It also mentions The Secret Diary of Laura Palmer, which was written by Lynch's daughter Jennifer and published in October 1990 in between airing of the first and second seasons of the Twin Peaks series. The chapter details the The Secret Diary's initial release that reached number four on The New York Times bestseller list during the height of Twin Peaks mania. It explains book stands as a powerful testimony of the harmful and damaging effects of sexual abuse.

scholarly journals Movie Recommendation System Mistreatment Current Trends and Sentiment Analysis from Micro Blogging Knowledge

2021 ◽  
Vol 9 (11) ◽  
pp. 393-398
Author(s):  
J Manikandan
Keyword(s):  
Collaborative Filtering ◽  
Sentiment Analysis ◽  
Digital Media ◽  
Recommendation System ◽  
The Public ◽  
Public Sentiment ◽  
Current Trends ◽  
Traditional Approaches ◽  
User History ◽  
Content Based Filtering

Abstract: Recommendation systems (RSs) have garnered immense interest for applications in e-commerce and digital media. Traditional approaches in RSs include such as collaborative filtering (CF) and content-based filtering (CBF) through these approaches that have certain limitations, such as the necessity of prior user history and habits for performing the task of recommendation. To minimize the effect of such limitation, this article proposes a hybrid RS for the movies that leverage the best of concepts used from CF and CBF along with sentiment analysis of tweets from microblogging sites. The purpose to use movie tweets is to understand the current trends, public sentiment, and user response of the movie. Experiments conducted on the public database have yielded promising results. Keywords: Collaborative filtering, Content based filtering, Recommendation System, Sentiment Analysis, Twitter

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