Relevant bibliographies by topics / Movie Classification

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Movie Classification'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Movie Classification"

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Dwivedi, Somya, Harsh Patel, and Shweta Sharma. "Movie Reviews Classification Using Sentiment Analysis." Indian Journal of Science and Technology 12, no. 41 (2019): 1–6. http://dx.doi.org/10.17485/ijst/2019/v12i41/145554.

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Topal, Kamil, and Gultekin Ozsoyoglu. "Emotional classification and visualization of movies based on their IMDb reviews." Information Discovery and Delivery 45, no. 3 (2017): 149–58. http://dx.doi.org/10.1108/idd-05-2017-0045.

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Purpose The purpose of this study is to detect these reviews’ complex emotions, visualize and analyze them. Movie reviewers’ moviescores and reviews can be analyzed with respect to their emotion content, aggregated and projected onto a movie, resulting in an emotion map for a movie. It is then possible for a moviegoer to choose a movie, not only on the basis of movie scores and reviews, but also on the basis of aggregated emotional outcome of a movie as reflected by its emotion map displaying certain emotion map patterns desirable for the moviegoer. Design/methodology/approach The authors use
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Sabrina, Fira, and Winanda Aghniya Puteri. "analysis of the onomatopoeia in “COCO” movie." LADU: Journal of Languages and Education 2, no. 4 (2022): 147–51. http://dx.doi.org/10.56724/ladu.v2i4.101.

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Background: when people watch movies, they not only enjoy the pictures and the action but also related to linguistic expression. One of them is onomatopoeia, which makes dialogue in the film becomes more interesting. Purpose: This research aims to describe kind of onomatopoeic words used in the COCO movie. Design and methods: This method of this research was a descriptive qualitative research. The data were analyzed for collecting the primary and secondary onomatopoeia. In collecting the data for the analysis the source data was taken from the movie entitled “COCO”. In collecting data, at this
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Neetu, Singh, Rajput Rahul, Jaggi Muskan, and Bhatia Rohan. "Movie Genre Classification through Movie posters using Deep Learning techniques." International Journal of Advance and Applied Research 4, no. 32 (2023): 61–65. https://doi.org/10.5281/zenodo.8434380.

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<strong>Abstract</strong><strong>:</strong> The classification of movie genres is a crucial task in the film industry for various purposes, such as recommendation systems, content analysis, and marketing strategies. Traditional methods primarily rely on textual features and metadata, which may not capture the visual essence of a movie accurately. In this research paper, we propose an IMDb genre classifier that utilizes movie posters as input through deep learning techniques. We demonstrate the effectiveness of our approach by training and evaluating a deep neural network on a large-scale datas
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Kadurhalli Sangappa, Jyothi, and Shantala Chikkanaravangala Paramashivaia. "Multi-domain aspect-oriented sentiment analysis for movie recommendations using feature extraction." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 2 (2024): 1216. http://dx.doi.org/10.11591/ijeecs.v33.i2.pp1216-1223.

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&lt;span&gt;Sentiment analysis is a well-recognized research field that has acknowledged significant attention in recent years. Researchers have made extensive efforts in employing various methodologies to explore these domains. Sentiment classification plays a fundamental role in natural language processing (NLP). However, studies have shown that sentiment classification models heavily depend on the specific domain. In the context of movie industry, where the demand for reliable movie reviews is high and not all movies are of exceptional quality and worthy of viewers time. Therefore, people d
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Sangappa, Jyothi Kadurhalli, and Shantala Chikkanaravangala Paramashivaia. "Multi-domain aspect-oriented sentiment analysis for movie recommendations using feature extraction." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 2 (2024): 1216–23. https://doi.org/10.11591/ijeecs.v33.i2.pp1216-1223.

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Sentiment analysis is a well-recognized research field that has acknowledged significant attention in recent years. Researchers have made extensive efforts in employing various methodologies to explore these domains. Sentiment classification plays a fundamental role in natural language processing (NLP). However, studies have shown that sentiment classification models heavily depend on the specific domain. In the context of movie industry, where the demand for reliable movie reviews is high and not all movies are of exceptional quality and worthy of viewers time. Therefore, people depend on mov
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Narawade, Vaibhav, Aneesh Potnis, Vishwaroop Ray, and Pratik Rathor. "Movie Posters’ Classification into Multiple Genres." ITM Web of Conferences 40 (2021): 03048. http://dx.doi.org/10.1051/itmconf/20214003048.

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Our project intends to classify movies into the three most probable genres that they belong to, from a predefined set of 25 genres, based on only one image i.e the movie poster. We have made use of Convolutional Neural Networks (CNN) to realize this project as we believe it would be of help to extract the features and visual information from the image. Instead of a multi-class classification problem in which the input is classified into any one class, this project would be more correctly described as a multilabel classification problem as a movie belongs to more than one genre. In this project
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Preksha, Khant, and Tidke Bharat. "Multimodal Approach to Recommend Movie Genres Based on Multi Datasets." Indian Journal of Science and Technology 16, no. 30 (2023): 2304–10. https://doi.org/10.17485/IJST/v16i30.1238.

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Abstract <strong>Objectives:</strong>&nbsp;The main purpose of this study is to implement the multimodal as well as the multilabel approach of accurate movie genre classification using the Actor, Director, Writer, Poster Images, and Synopsis data. The various kind of data collected from IMDB as well as existing datasets are used to train the models.<strong>&nbsp;Methods:</strong>&nbsp;The 5 deep learning models are created on Poster Images, Text Data, Actors Data, Directors Data, and Writers Data. These models are then combined using the weighted average ensemble model of deep learning. The fi
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Jhalani, Ritu, Harshita Virwani, Divyanshi Goyal, and Somya Vashishtha. "Prediction of Movie Success Using Classification." Indian Journal of Computer Science 3, no. 6 (2019): 1. http://dx.doi.org/10.17010/ijcs/2018/v3/i6/141443.

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Popat, Anannya, Lakshya Gupta, Gowri Namratha Meedinti, and Boominathan Perumal. "Movie Poster Classification Using Federated Learning." Procedia Computer Science 218 (2023): 2007–17. http://dx.doi.org/10.1016/j.procs.2023.01.177.

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Dissertations / Theses on the topic "Movie Classification"

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Zhang, Jun. "Sentiment analysis of movie reviews in Chinese." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412670.

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Sentiment analysis aims at figuring out the opinions of the users towards a certain service or product. In this research, the aim is at classifying the sentiments of users based on the comments they have posed on Douban movie website. In this thesis, I try two different ways to classify the sentiments: with the first one classifying comments into five classes of ratings from 1 to 5, and with the second one classifying comments into three classes of ratings: negative, neutral and positive. For the latter, the ratings of 1 and 2 are grouped as negative, the ratings of 3 neutral and the ratings o
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Sarika, Pawan Kumar. "Comparing LSTM and GRU for Multiclass Sentiment Analysis of Movie Reviews." Thesis, Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20213.

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Today, we are living in a data-driven world. Due to a surge in data generation, there is a need for efficient and accurate techniques to analyze data. One such kind of data which is needed to be analyzed are text reviews given for movies. Rather than classifying the reviews as positive or negative, we will classify the sentiment of the reviews on the scale of one to ten. In doing so, we will compare two recurrent neural network algorithms Long short term memory(LSTM) and Gated recurrent unit(GRU). The main objective of this study is to compare the accuracies of LSTM and GRU models. For trainin
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Sommar, Fredrik, and Milosz Wielondek. "Combining Lexicon- and Learning-based Approaches for Improved Performance and Convenience in Sentiment Classification." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166430.

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Sentiment classification is the process of categorizing data into categories based on its polarity with a wide array of applications across several industries. This report examines a combination of two prominent approaches to sentiment classification using a lexicon of weighted words and machine learning respectively. These approaches are compared with the combined hybrid approach in order to give an account of their relative strengths and weaknesses. When run on a set of IMDb movie reviews the results indicate that the hybrid model performs better than the lexicon-based approach, in turn bein
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Usbeck, Frank. ""Don’t Forget about Us, Because We Can’t Forget You": A Narrative Approach to the Concept of ‘Community’ in American Soldier Blogs." Leipziger Universitätsverlag, 2012. https://tud.qucosa.de/id/qucosa%3A29205.

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The following contribution interweaves culturalanthropological and media studies approaches to analyze the concept of 'community' in a phenomenon of the new media, the socalled 'milblogs.' These communities use the blogosphere to create and distribute a master arrative about the relationship of American civil society with its military and, thus, about how segments of American society attempt to come to terms with the War on Terror. The contribution emphasizes the interaction of bloggers with their audience in the narrative process of imagining, proclaiming, and nurturing such communities.
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Herrmann, Sebastian M., Katja Kanzler, and Frank Usbeck. "Participating Audiences, Imagined Public Spheres: The Cultural Work of Contemporary American(ized) Narratives - Introduction." Leipziger Universitätsverlag, 2012. https://tud.qucosa.de/id/qucosa%3A29206.

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This is a book about contemporary American(ized) narratives and the audiences they call into being. It brings together eight very diverse case studies covering and investigating a wide range of media, genres, and modes to ask how contemporary 'texts' encourage 'imagined communities' of readers/viewers that operate as 'public spheres' of social and political deliberation, self-fashioning, and debate. In asking this question, the contributions collected in this volume shift perspectives in a number of ways: They question the boundary between the audiences of (often popular and broadly circulat
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Usbeck, Frank. "The Power of the Story: "Popular Narratology" in Pentagon Reports on Social Media Use in the Military." Universitätsverlag Winter, 2015. https://tud.qucosa.de/id/qucosa%3A29673.

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This contribution explores notions of "popular narratology" in reports, memos and strategic research papers of the US military and affiliated institutions. It investigates the military´s analysis of emerging social media practices and corresponding efforts to adapt military organization, strategy, and culture to these new technological and cultural phenomena. Employing notions and techniques of constructing and disseminating a narrative that they borrow from literary theory, media studies, and advertising, these texts negotiate best practices to set political agendas and instigate institution
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Evans, Richard Kent. "MOVE: RELIGION, SECULARISM, AND THE POLITICS OF CLASSIFICATION." Diss., Temple University Libraries, 2018. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/505910.

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History<br>Ph.D.<br>This dissertation is a study of how religion is manufactured, policed, imagined, and defended in the modern United States. It traces the history of one group, MOVE, from its inception in the late 1960s to the present in order to illustrate how the category of religion functions in the modern United States. The central premise of the book is that MOVE people believed MOVE was a religion. They believed, nearly from the very beginning of the group, that John Africa was a prophet who communicated on behalf of the divine, that his Teachings were inspired and had supernatural eff
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Saxton, Michael J. "Move, dither, move, dither: on the structure of random walks and single-particle trajectories." Diffusion fundamentals 16 (2011) 30, S. 1-2, 2011. https://ul.qucosa.de/id/qucosa%3A13763.

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Kato, Jien, Toyohide Watanabe, Sebastien Joga, et al. "An HMM-based segmentation method for traffic monitoring movies." IEEE, 2002. http://hdl.handle.net/2237/6744.

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Goernert, Christiane. "Pietro Germis kritischer Blick auf das tradierte Konzept von Männlichkeit und Weiblichkeit in \"Divorzio all\'italiana\" und \"Sedotta e abbandonata\" unter dem Aspekt des sizilianischen Ehrenkodex." Master's thesis, Universitätsbibliothek Leipzig, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-124504.

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In dieser Arbeit soll es um die Ehre gehen, insbesondere um die kritische Auseinandersetzung mit den komplexen Regeln des Ehrenkodex in zwei Filmen des italienischen Regisseurs Pietro Germi, Divorzio all\'italiana (F/I 1961, Scheidung auf italienisch) und Sedotta e abbandonata ( F/I 1963, Verführung auf italienisch, DDR-Titel: \"Verführung auf sizilianisch\"). Die beiden Filme gehören zusammen mit Signore & Signori (F/I 1965, Aber, aber meine Herren...) zu einer Trilogie, mit der Germi die Verlogenheit und die Mängel der italienischen Gesellschaft angreift und karikiert. Alle drei Filme wurden
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Books on the topic "Movie Classification"

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Philippines. Intellectual Property Code of the Philippines: Updated IRRs and related laws : other laws included: Movie and Television Review and Classification Board (PD 1986), Videogram Regulatory Board (PD 1987), Children's Television Act of 1997 (RA 8370), Art. 201, RPC, and LOI 13, etc. 2nd ed. Edited by Central Book Supply Inc. Published & distributed by Central Book Supply, 2001.

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Singer, Ruth. Beyond the classifier/gender dichotomy. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198795438.003.0005.

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The entrenched nature of the gender/classifier dichotomy stands in the way of better typologies of nominal classification. How can we move beyond it to a more integrated view of nominal classification? Looking at a range of kinds of data from the Australian language Mawng, it is clear that our understanding of many less well-known nominal classification systems reflects a lack of data on how the system is used. Mawng has what seems like a well-behaved system of five genders, including gender agreement in the verb. However, the genders, like classifiers, play a crucial role in constructing mean
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Barkataki-Ruscheweyh, Meenaxi. Getting Acquainted with the Tangsa. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199472598.003.0003.

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Chapter 3 focuses on the Tangsa, and discusses their linguistic and ethnic classification into sub-groups such as the Pangwa, their relation to the Naga and the Singpho, as well as some of their ‘traditional’ practices, their festivals, their lifestyles and their social and cultural traditions. Starting with the past, I end in the present by describing the changes that have come to their lives with their move down the hills, their conversion to Christianity and their gradual move to a ‘modern’ style of living. The last section of the chapter describes my own introduction to the Tangsa and my f
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Stern, Rowena, Heather Esson, and Cecilia Balestreri. Phytoplankton: Flagellates. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199233267.003.0014.

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This chapter describes the taxonomy of flagellates. Marine flagellates is an all-inclusive term which describes a plethora of different protist species scattered throughout different eukaryotic lineages that move using their flagella. Many flagellates also have other morphological life stages, but the chapter focuses on those taxa for which the flagellated form is predominant. It covers their life cycle, ecology and distribution, and toxic species. It includes a section that indicates the systematic placement of the taxon described within the tree of life, and lists the key marine representati
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Chamoreau, Claudine. Purepecha, a Polysynthetic but Predominantly Dependent-Marking Language. Edited by Michael Fortescue, Marianne Mithun, and Nicholas Evans. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199683208.013.38.

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Purepecha (language isolate, Mexico) has one relevant characteristic that leads to identifying it as a polysynthetic language: productive verbal morphology (in particular locative suffixes). Purepecha is a predominantly dependent-marking language, as its pronominal markers are enclitics, generally second position enclitics. But, in some contexts Purepecha shows head-marking characteristics. Today, pronominal enclitics exhibit variation, tending to move to the rightmost position in the clause; they may encliticize to the predicate itself, showing a head-attraction or polypersonalism strategy an
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S. T. (Samuel Truesdale) 182 Livermore. Checkers Improved: Over 200 Games And Problems, Laws Of The Game, The Move, Classification, Explanations, Etc. For The New Board Without Checks, And The Old Board With Its 64 Checks. Franklin Classics, 2018.

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S. T. (Samuel Truesdale) 182 Livermore. Checkers Improved: Over 200 Games and Problems, Laws of the Game, the Move, Classification, Explanations, etc. for the New Board Without Checks, and the Old Board with Its 64 Checks. Creative Media Partners, LLC, 2018.

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S T (Samuel Truesdale) 182 Livermore. Checkers Improved: Over 200 Games and Problems, Laws of the Game, the Move, Classification, Explanations, Etc. for the New Board Without Checks, and the Old Board with Its 64 Checks. Franklin Classics Trade Press, 2018.

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Milne, Nicola, and Teffy Thomas. Oxford Handbook of Diabetes Nursing. 2nd ed. Oxford University PressOxford, 2025. https://doi.org/10.1093/med/9780198831846.001.0001.

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Abstract This new edition of the Oxford Diabetes Nursing Handbook serves to provide education for the holistic and gold standard of care for all adults living with diabetes. The initial chapters recap on relevant anatomy and physiology proceeding to then detail diagnosis and classification. There is specific coverage of both type 1 and type 2 diabetes and within the section on type 2 diabetes, there is consideration of prevention and possible remission ahead of details on medications which extends to the safe and appropriate use of insulin. New for this edition, is inclusion of the psychologic
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Book chapters on the topic "Movie Classification"

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Ivasic-Kos, Marina, Miran Pobar, and Ivo Ipsic. "Automatic Movie Posters Classification into Genres." In ICT Innovations 2014. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-09879-1_32.

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Hong, Hao-Zhi, and Jen-Ing G. Hwang. "Multimodal PLSA for Movie Genre Classification." In Multiple Classifier Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20248-8_14.

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Gunter, Barrie. "What Is the Impact of Regulatory Classification?" In Predicting Movie Success at the Box Office. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71803-3_8.

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Ghaemmaghami, Pouya, Mojtaba Khomami Abadi, Seyed Mostafa Kia, Paolo Avesani, and Nicu Sebe. "Movie Genre Classification by Exploiting MEG Brain Signals." In Image Analysis and Processing — ICIAP 2015. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23231-7_61.

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Thet, Tun Thura, Jin-Cheon Na, and Christopher S. G. Khoo. "Sentiment Classification of Movie Reviews Using Multiple Perspectives." In Digital Libraries: Universal and Ubiquitous Access to Information. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89533-6_19.

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Basha, Syed Muzamil, Dharmendra Singh Rajput, T. P. Thabitha, P. Srikanth, and C. S. Pavan Kumar. "Classification of Sentiments from Movie Reviews Using KNIME." In Proceedings of the 2nd International Conference on Data Engineering and Communication Technology. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1610-4_64.

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Shambharkar, Prashant Giridhar, Gaurang Mehrotra, Kanishk Singh Thakur, Kaushal Thakare, and Mohammad Nazmud Doja. "Multi-Class Classification of Actors in Movie Trailers." In Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-7533-4_77.

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Bi, Tianyu, Dimitri Jarnikov, and Johan Lukkien. "Shot-Based Hybrid Fusion for Movie Genre Classification." In Image Analysis and Processing – ICIAP 2022. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06427-2_22.

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Hasan, Muhammad Abul, Min Xu, Xiangjian He, and Ling Chen. "Shot Classification Using Domain Specific Features for Movie Management." In Database Systems for Advanced Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29035-0_28.

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Islam, Md Mohaiminul, and Gedas Bertasius. "Long Movie Clip Classification with State-Space Video Models." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19833-5_6.

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Conference papers on the topic "Movie Classification"

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Lafhel, Majda, Mohammed El Hassouni, and Hacine Cherifi. "Learning Character Network Features for Movie Genre Classification." In 2024 IEEE Thirteenth International Conference on Image Processing Theory, Tools and Applications (IPTA). IEEE, 2024. http://dx.doi.org/10.1109/ipta62886.2024.10755944.

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R, Swathi, Aiswaryaa Sri, and Padma Roshini. "Sentiment Classification of Movie Reviews with Logistic Regression." In 2024 International Conference on Sustainable Communication Networks and Application (ICSCNA). IEEE, 2024. https://doi.org/10.1109/icscna63714.2024.10863969.

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Kalamkar, Pratik N., and Yogesh Kumar Sharma. "Blend of VADER and TextBlob for Movie Script Classification." In 2024 4th International Conference on Artificial Intelligence, Robotics, and Communication (ICAIRC). IEEE, 2024. https://doi.org/10.1109/icairc64177.2024.10899931.

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Srivastava, Anand Prakash, and Sanjeev Kumar Sharma. "Modelling a movie recommendation system using a mixed classification method." In 2024 1st International Conference on Advanced Computing and Emerging Technologies (ACET). IEEE, 2024. http://dx.doi.org/10.1109/acet61898.2024.10730631.

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Visutsak, Porawat, Fuangfar Pensiri, Ponrudee Netisopakul, et al. "Genre Classification of Movie Trailers using Spectrogram Analysis and Machine Learning." In 2024 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom). IEEE, 2024. http://dx.doi.org/10.1109/blackseacom61746.2024.10646256.

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Choukotiya, Ankit, and Sandeep Kumar Tiwari. "Emotion-Based Movie Reviews Classification Using Deep Learning and Facial Image Recognition." In 2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0. IEEE, 2024. http://dx.doi.org/10.1109/otcon60325.2024.10688144.

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AbdElminaam, Diaa Salama, Amr Mohamed Mahmoud, Mohamed Ehab Anwar, Abdelrahman Abdelmageed Ahmed, and Abdelrahman Mohamed Abdelfattah. "Improving Movie Review Sentiment Classification Through Advanced Machine Learning Models: A Comparative Study." In 2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC). IEEE, 2024. https://doi.org/10.1109/miucc62295.2024.10783560.

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N S, Malavika, Gouripriya Murali, and Vimina E R. "Sentiment Analysis of Movie Reviews with Transformer Models: A Deep Learning Approach to Text Classification." In 2025 5th International Conference on Pervasive Computing and Social Networking (ICPCSN). IEEE, 2025. https://doi.org/10.1109/icpcsn65854.2025.11035830.

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Islam, Md Touhidul, Farjana Parvin, Saad Ahmed Sazan, and Tariq Bin Amir. "Comparative Analysis of Sentiment Classification on IMDB 50k Movie Reviews: A Study Using CNN, LSTM, CNN-LSTM, and BERT Models." In 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON). IEEE, 2024. https://doi.org/10.1109/peeiacon63629.2024.10800035.

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Joshi, Shreehar, Eman Abdelfattah, and Ryan Osgood. "Classification of Movie Success: A Comparison of Two Movie Datasets." In 2022 IEEE World AI IoT Congress (AIIoT). IEEE, 2022. http://dx.doi.org/10.1109/aiiot54504.2022.9817158.

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Reports on the topic "Movie Classification"

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Hooten, Christopher, and Carlo Pietrobelli. CMF in Review: 2006-2011. Inter-American Development Bank, 2012. http://dx.doi.org/10.18235/0006906.

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This paper presents a retrospective review of several key areas of work of the Capital Markets and Financial Institutions Division (CMF) of the Inter-American Development Bank. Presented with each chapter as an independent piece, the paper analyzes the operations portfolio of CMF from 2006 to 2011 drawing on a unique classification system developed in conjunction with the Division's internal Operations and Project Database. The goal of this database and paper is to move beyond the existing analytical frameworks of the bank to a more conceptual framework that looks at the fundamental goals and
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Lasko, Kristofer, and Sean Griffin. Monitoring Ecological Restoration with Imagery Tools (MERIT) : Python-based decision support tools integrated into ArcGIS for satellite and UAS image processing, analysis, and classification. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40262.

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Monitoring the impacts of ecosystem restoration strategies requires both short-term and long-term land surface monitoring. The combined use of unmanned aerial systems (UAS) and satellite imagery enable effective landscape and natural resource management. However, processing, analyzing, and creating derivative imagery products can be time consuming, manually intensive, and cost prohibitive. In order to provide fast, accurate, and standardized UAS and satellite imagery processing, we have developed a suite of easy-to-use tools integrated into the graphical user interface (GUI) of ArcMap and ArcG
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Solomin, Eugen. SOVIET-RUSSIAN PROPAGANDA AS A WAY TO PROMOTE NARRATIVES AND INTERFERE IN THE INFORMATION SPACE: REGIONAL ASPECT. Ivan Franko National University of Lviv, 2024. http://dx.doi.org/10.30970/vjo.2024.54-55.12152.

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The article updates the activities of regional broadcasters in the information space of the Luhansk region, where numerous enemy information attacks preceded the invasion of the Russian occupation forces. Main objective of the study - mass media activities of the Luhansk region’s television companies in the pre-war and post-war periods and the specifics of the integration of the (pro) Russian agenda into the region’s information space. The study was done out using a descriptive, classification, comparative-historical method, which made it possible to consider the regional telespace in the cont
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