Дисертації з теми "The Half of It Movie"
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McGinley, Susan. "Half Full or Half Empty?" College of Agriculture, University of Arizona (Tucson, AZ), 1993. http://hdl.handle.net/10150/295739.
Повний текст джерелаGonring, Gabriel Menotti M. P. "Movie/cinema : rearrangements of the apparatus in contemporary movie circulation." Thesis, Goldsmiths College (University of London), 2011. http://research.gold.ac.uk/6604/.
Повний текст джерелаKalantari, Amir. "Making the movie." Thesis, University of Skövde, School of Humanities and Informatics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-3868.
Повний текст джерелаGrell, Laura Lynn. "EZ-Viz movie /." Online version of thesis, 2007. http://hdl.handle.net/1850/5701.
Повний текст джерелаHalliday, Laura Jo. "Such is Furphy : half bushman, half bookworm /." Available to subscribers only, 2005. http://proquest.umi.com/pqdweb?did=1068242541&sid=21&Fmt=2&clientId=1509&RQT=309&VName=PQD.
Повний текст джерелаCakiroglu, Seda. "Suggest Me A Movie: A Multi-client Movie Recommendation Application On Facebook." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612084/index.pdf.
Повний текст джерелаPollack, Alexander Gregory. "Half-virgin." Master's thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5010.
Повний текст джерелаID: 029809539; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Includes reading list (p. 156-159).; Thesis (M.F.A.)--University of Central Florida, 2011.
M.F.A.
Masters
English
Arts and Humanities
Creative Writing
Arikatla, Govardhan, and Bhargav Chinnapottu. "Movie prediction based on movie scriptsusing Natural Language Processing and Machine Learning Algorithms." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-21761.
Повний текст джерелаHansson, Henri. "3D modelling of a Laser Welding Cell for movie presentation : making of the movie." Thesis, University West, Department of Engineering Science, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-721.
Повний текст джерелаThis report describes a Bachelor thesis work in which a robotised laser welding cell has been modelled and simulated for the purpose of making a presentation movie. The report shows that the work has been concentrated on making the movie from the modelling phase through the recording of the movie and ending up with the editing of the final presentation movie. A pre-study was made prior the Bachelor thesis work. In the pre-study a literature study was conducted about measurement and calibration of a welding cell. Measurement of almost all equipment in the entire cell was also conducted in the pre-study. The main result of this pre-study is a thorough investigation of what objects and functions that needs to be modelled in order to explain the functions in the specific laser welding cell The purpose for this Bachelor thesis work is to give an efficient and alternative way to present a laser welding cell that resides in Production Technology Centre (PTC) at Innovatum, Trollhättan Sweden. The movie can be used outside PTC or if the laser welding cell is occupied with work, since it is not allowed to be inside the cell when in progress. The result of this work is a nearly 12 minute long presentation movie which shows all predefined elements of the cell together with a real welding sequence with metal deposition (MD).
Ivarsson, Jakob, and Mathias Lindgren. "Movie recommendations using matrix factorization." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186400.
Повний текст джерелаRoghult, Alexander. "Chatbot trained on movie dialogue." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157637.
Повний текст джерелаLeonardo, Ágata. "Movie Marketing: o caso português." Master's thesis, Faculdade de Ciências Sociais e Humanas, Universidade Nova de Lisboa, 2010. http://hdl.handle.net/10362/7012.
Повний текст джерелаA arte cinematográfica, quase desde o seu nascimento, teve necessidade de se auto-promover, sendo que cada vez mais se pode considerar essa publicitação uma arte em si mesma. Mais de metade dos filmes produzidos anualmente fazem parte do cinema mainstream. Estes, antes de um produto artístico, são um produto que necessita garantir a sua rentabilidade, sendo essencial salvaguardar e aumentar o número de espectadores. Os filmes começam a ser anunciados semanas, ou mesmo meses antes da estreia, criando complexas campanhas publicitárias, garantindo que não só o público alvo toma conhecimento da existência de determinado filme, mas sim o maior número de potenciais espectadores - consumidores de filmes. Os meios para a divulgação são variados, a publicidade televisiva, os sites (meios de comunicação cada vez mais utilizados), os “tradicionais” trailers, os outdoors que interpelam até o transeunte mais alheio, ou mesmo as magazines, em publicações especializadas, ou não. Visto isto, e se a publicidade reconhece o filme enquanto elemento importante do complexo processo de propaganda, também o contrário deveria acontecer – algo que só sucede nas maiores industrias da área. Assim sendo, desenvolve-se neste trabalho uma análise crítica da dupla relação entre cinema/ marketing, e espectador/ marketing, com base no público do cinema português, observando e comentando, em paralelo, o envolvente global da indústria cinematográfica.
Andersson, Moa, and Lisa Tran. "Predicting movie Ratings using KNN." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280330.
Повний текст джерелаMånga tjänster föreser rekommendationer till deras användare för att göra det enkelt att hitta relevant information. Det är därför viktigt för dessa tjänster att utveckla rekommendationssystem till att bli bättre. Genom användning av ny teknik är det vanligt att implementera rekommendationssystem som baserar sig på maskininlärning. I denna rapport undersökes en metod för att förutspå tittares betygsättning av filmer baserat på maskininlärningsalgoritmen K-nearest neighbors, eller KNN. Ytterligare jämfördes systemet med användningen av en referensmetod som använder medelvärdet av alla användares betygsättning som förutsägelser. Studiens ändamål var att analysera användbarheten av KNN. Slutsatsen var att implementation av ett rekommendationssystem för filmer baserat på KNN algoritmen genererade ett bättre resultat än referensmetoden.
Vaughan, Nicola. "From buddy movie to bromance." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/12116.
Повний текст джерелаHinas, Toni, and Isabelle Ton. "Recommender Systems for Movie Recommendations." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239376.
Повний текст джерелаGorinski, Philip John. "Automatic movie analysis and summarisation." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31053.
Повний текст джерелаGoulden, Jan. "The western, the buddy movie and noir : lesbian re-readings of the American action movie." n.p, 1999. http://library7.open.ac.uk/abstracts/page.php?thesisid=13.
Повний текст джерелаPagliughi, Rya C. "half-matter self." Connect to online resource, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1442909.
Повний текст джерелаMbamba, Saleh. "Half a Gemini." Thesis, Malmö högskola, Fakulteten för lärande och samhälle (LS), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-30854.
Повний текст джерелаBeifield, Adam. "The Half House." Thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/34886.
Повний текст джерелаMaster of Architecture
Christensen, Holly. "Half a Dream." Kent State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=kent1291149684.
Повний текст джерелаMelnyk, Veronica. "'Half fashion and half passion' : the life of publisher Henry Colburn." Thesis, University of Birmingham, 2002. http://etheses.bham.ac.uk//id/eprint/163/.
Повний текст джерелаBaranowski, Andreas M. [Verfasser]. "Cognitive movie psychology : effects of sound, 3D, and viewing context on movie perception / Andreas M. Baranowski." Mainz : Universitätsbibliothek Mainz, 2016. http://d-nb.info/1121333540/34.
Повний текст джерелаFiskaa, Sverre, and n/a. "Road Maps - Navigating the Road Movie." RMIT University. Creative Writing, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080627.154735.
Повний текст джерелаPinsonneault, Michael. "Social dimensions of Hollywood movie music." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0020/NQ43591.pdf.
Повний текст джерелаNguyen, Nhat-Tan. "Human motion tracking from movie sequences." Thesis, Université Laval, 2011. http://www.theses.ulaval.ca/2011/28170/28170.pdf.
Повний текст джерелаBhargav, Suvir. "Efficient Features for Movie Recommendation Systems." Thesis, KTH, Kommunikationsteori, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-155137.
Повний текст джерелаGuerra, Marvin J. "Creating a three dimensional holographic movie." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/46124.
Повний текст джерелаIncludes bibliographical references (leaves 47-48).
An experimental study was carried out on the ability to create a three-dimensional holographic movie. Holograms were written on VRP-M emulsion film with the green line of an Argon-Ion laser. The type of hologram write setup favored was a reflection hologram, due to its artistic capabilities. The illusion of a floating image is much better produced by reflection holograms as opposed to transmission holograms. However, due to the thinness of the film, white light readout was not possible, and the reading setup included the original writing laser. Although successful holograms were written on sheets with same emulsion as the final roll film, the final product on the roll of film did not result as expected due to a failure in the development process. This paper will describe the setup that I created, discuss the aspects of the process that turned out well and suggest improvements to achieve a successful experiment in the future.
by Marvin J. Guerra.
M.Eng.
Sanchez, Tani Dianca. "Race and the Matrix Movie Trilogy." Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/215411.
Повний текст джерелаSolanki, Sandeep. "Engineering enhancements for movie recommender systems." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/13621.
Повний текст джерелаDepartment of Computing and Information Sciences
Doina Caragea
The evolution of the World Wide Web has resulted in extremely large amounts of information. As a consequence, users are faced with the problem of information overload: they have difficulty in identifying and selecting items of interest to them, such as books, movies, blogs, bookmarks, etc. Recommender systems can be used to address the information over-load problem by suggesting potentially interesting or useful items to users. Many existing recommender systems rely on the collaborative filtering technology. Among other domains, collaborative filtering systems have been widely used in e-commerce and they have proven to be very successful. However, in recent years the number of users and items available in e-commerce has grown tremendously, challenging recommender systems with scalability issues. To address such issues, we use canopy/clustering techniques and Hadoop MapReduce distributed framework to implement user-based and item-based recommender systems. We evaluate our implementations in the context of movie recommendation. Generally, standard rating prediction schemes work by identifying similar users/items. We propose a novel rating prediction scheme, which makes use of dissimilar users/items, in addition to the similar ones, and experimentally show that the new prediction scheme produces better results than the standard prediction scheme. Finally, we engineer two new approaches for clustering-based collaborative filtering that can make use of movie synopsis and user information. Specifically, in the first approach, we perform user-based clustering using movie synopsis, together with user demographic data. In the second approach, we perform item-based clustering using movie synopsis, together with user quotes about movies. Experimental results show that the movie synopsis and user demographic data can be effectively used to improve the rating predictions made by a recommender system. However, user quotes are too vague and do not produce better predictions.
Wu, Yuk Ying. "Movie allocation in parallel video servers /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?COMP%202002%20WU.
Повний текст джерелаIncludes bibliographical references (leaves 69-76). Also available in electronic version. Access restricted to campus users.
Chiu, Chun-Kai. "Movie theater ticket order system: (MTTOS)." CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2541.
Повний текст джерелаWand, Ann Elizabeth Lewis. "Half spaghetti - half Knodel : cultural division through the lens of language learning." Thesis, University of Oxford, 2016. http://ora.ox.ac.uk/objects/uuid:d6391d08-30ea-4b78-8fce-c7ac684eb74a.
Повний текст джерелаSorokin, Anissa Jane. "Constructing dialogue, constructing identites mixed heritage identity construction in half and half /." Connect to Electronic Thesis (CONTENTdm), 2009. http://worldcat.org/oclc/456417685/viewonline.
Повний текст джерелаHennessy, Mark Thomas. "The Half-Way House." NCSU, 2006. http://www.lib.ncsu.edu/theses/available/etd-04252006-075117/.
Повний текст джерелаMoros-Achong, Keren. "A Half-Dreamed Dream." NSUWorks, 2015. http://nsuworks.nova.edu/writing_etd/26.
Повний текст джерелаMcMullin, Jordan. "Dim Half-Lights: Stories." Miami University / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=miami1070563805.
Повний текст джерелаSherman, Katharine. "Half sick of shadows." Thesis, University of Iowa, 2013. https://ir.uiowa.edu/etd/2631.
Повний текст джерелаJaekel, Kathryn S. "A tale of a "half fairy, half imp" the rape of Jane Eyre /." [Ames, Iowa : Iowa State University], 2007.
Знайти повний текст джерелаAndersson, Elisabeth, and Maria Hansson. "IFÖ - The perception through a corporate movie." Thesis, Kristianstad University College, Department of Business Administration, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-3269.
Повний текст джерелаThe picture a company sends out is important. Corporate identity, corporate image and the corporate communication are three concepts linked together. The purpose with this dissertation was to examine a corporate movie done by Ifö, a company producing bath and toilet equipment, by looking at its identity, image and communication. A deductive approached was used and in the theoretical framework an introduction regarding marketing was first presented. Further different theories and models were discussed with focus on the Operational model by Gray & Balmer and also the spiderweb developed by Bernstein. This model was also modified to give a clear picture of how Ifö is perceived.
In the beginning of the dissertation an interview was done with the marketing director at Ifö, which was a base for the questionnaire survey. This was distributed to investigate the perception of Ifö from its stakeholders. Different attributes were decided to represent the corporate identity of the company Ifö. The result showed that the stakeholders in general perceived Ifö in the same way as Ifö wanted them to do except in some attributes where Ifö has sent out a more confused picture.
Kirmemis, Oznur. "Openmore: A Content-based Movie Recommendation System." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609479/index.pdf.
Повний текст джерелаMa, Ke. "Content-based Recommender System for Movie Website." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188494.
Повний текст джерелаRecommender System är ett verktyg som hjälper användarna att hitta innehåll och övervinna informationsöverflöd. Det förutspår användarnas intressen och gör rekommendation enligt räntemodellen användare. Den ursprungliga innehållsbaserade recommender är en fortsättning och utveckling av samarbete filtrering, som inte behöver användarens utvärdering artiklar. Istället är likheten beräknas baserat på informationen objekt som har varit valde av användare, och sedan göra rekommendationen därefter. Med förbättringen av maskininlärning, kan nuvarande innehållsbaserad recommender systemet bygga profil för användare och produkt respektive. Bygga eller uppdatera profilen enligt analysen av objekt som köps eller besöks av användare. Systemet kan jämföra användaren och profilen av artiklar och rekommendera den mest liknande produkt. Så här recommender metod som jämför användaren och produkten direkt kan inte föras in collaborative filtreringsmodell. Grunden för innehållsbaserad algoritm är förvärv och kvantitativ analys av innehållet. Eftersom forskning förvärv och filtrering av textinformation är mogen, många aktuella innehållsbaserade recommender system gör rekommendation enligt analysen av textinformation. Denna uppsats införa innehållsbaserad recommender system för film webbplats VionLabs. Det finns en mängd funktioner som extraherats från en film, är de mångfald och unik, vilket är också skillnaden med andra recommender system. Vi använder dessa funktioner för att konstruera film vektor och beräkna likheter. Vi introducerar en ny metod för att fastställa vikten av funktioner, vilket förbättrar företrädare för filmer. Slutligen utvärderar vi tillvägagångssättet för att illustrera förbättringen.
Jernbäcker, Carl, and Shahrivar Pojan. "Predicting movie success using machine learning techniques." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208506.
Повний текст джерелаOmrådet med att skapa prediktiva modeller med maskininlärning har ökat i storlek de senaste åren. Marknaden för filmer är stor med hundratals nya filmer skapade varje år. Syftet med denna rapport är att undersöka om det är möjligt att klassificera filmbetyg och brutto biljettförsäljing med metadata som är tillgängliga före utgåvan. Detta gjordes genom att bygga en klassificeringsmodell med metadata som erhållits från internet, såsom budget och vilka aktörer som är involverade etc. Denna studie lyckades korrekt förutsäga vilket betyg en film erhåller omkring 82% av fallen med den mest framgångsrika modell. I de utfallen där modellen misslyckades med att förutsäga rätt betyg, det var vanligtvis av en betygsklass, vilket motsvarade en avvikelse på ungefär 17%. När en förutsägelse för bruttoförsäljningen gjordes gav det ett positivt resultat av 15% av fallen. Resultaten av denna rapport är i viss utsträckning förenlig med tidigare studier med liknande metodik. Precisionen på förutsägelserna kan ökas med ett utökat data set med fler attribut
周穎琴 and Wing-kam Chow. "An analysis of Zhang Ailing's movie scripts." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B40676742.
Повний текст джерелаHitchcock, Stuart John. "The veneer of fear : understanding movie horror." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/402369/.
Повний текст джерелаZhang, 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.
Повний текст джерелаKuroptev, Roman, and Anton Lagerlöf. "Improving movie recommendations through social media matching." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20834.
Повний текст джерелаRecommender systems are a crucial part of navigating the vast number of products on the internet. Social media, in the form of Twitter microblogs, has been previously used to produce movie recommendations, yet this has mainly been to solve cold-start, a common problem in collaborative filtering environments. This work addresses how top-k recommendations in a collaborative filtering environment are affected when augmented with social media data. To answer this question a novel prototype is developed following a design science process model. This system re-ranks top-k recommendations based on a social matching process where Tweets are matched with movie keywords through latent semantic indexing (LSI) similarity. The prototype is evaluated through experiments regarding functionality, accuracy, consistency, and performance. The results show that NDCG and MAP metrics of the top-k recommendations improve with social matching compared to only using the collaborative filtering algorithms.
El, Aouad Sara. "Personalized, Aspect-based Summarization of Movie Reviews." Electronic Thesis or Diss., Sorbonne université, 2019. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2019SORUS019.pdf.
Повний текст джерелаOnline reviewing websites help users decide what to buy or places to go. These platforms allow users to express their opinions using numerical ratings as well as textual comments. The numerical ratings give a coarse idea of the service. On the other hand, textual comments give full details which is tedious for users to read. In this dissertation, we develop novel methods and algorithms to generate personalized, aspect-based summaries of movie reviews for a given user. The first problem we tackle is extracting a set of related words to an aspect from movie reviews. Our evaluation shows that our method is able to extract even unpopular terms that represent an aspect, such as compound terms or abbreviations, as opposed to the methods from the related work. We then study the problem of annotating sentences with aspects, and propose a new method that annotates sentences based on a similarity between the aspect signature and the terms in the sentence. The third problem we tackle is the generation of personalized, aspect-based summaries. We propose an optimization algorithm to maximize the coverage of the aspects the user is interested in and the representativeness of sentences in the summary subject to a length and similarity constraints. Finally, we perform three user studies that show that the approach we propose outperforms the state of art method for generating summaries
Lin, Szu-Yu, and 林思妤. "Online Movie Reviews: One's intention behind watching a movie." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/10633061647938522568.
Повний текст джерела國立交通大學
經營管理研究所
104
Since a long time age, word-of-mouth has always been an important way for people to exchange opinions and information. With the rising of the internet, electronic word-of-mouth(eWOM) shows up and gradually replaces traditional wordof-mouth. People tend to search for others’ experiences and sharing online in order to help them make purchase decisions or at least have a better idea of what they are intended to buy, especially for virtual products or services. Therefore, in this study, we would like to know more about the influence of eWOM to people’s intention of watching movies. Here, we discuss two dimensions of the movie review, which are the source(stranger or acquaintance) and the content feature(concrete or abstract). To do the study, we used a 2 X 2 between-subject design and gave out internet questionnaires to the mass population who are 18 to 50 years old in Taiwan. By using statistical analysis software SPSS 22, we conducted Reliability Analysis, Descriptive Analysis, Independent-Sample T Test and Regression Analysis with a valid sample size of 313. Our research results support our hypothesis that if the source is from an acquaintance and the content feature is concrete, people will have the most intention to watch the movie. In addition, acting abilities of the cast and people’s preference of movie genre will also stronger the positive influence on it.
Liu, Chih-Wei, and 劉志偉. "Active Object Movie." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/37243758184481638117.
Повний текст джерела國立東華大學
資訊工程學系
91
The objective of this thesis is to construct object movie with moving objects. In past researches, in order to allow the viewer to observe an object from any angle in a film, one had to utilize some expansive equipments in a special designed room. This thesis proposes to achieve the same goal with off-the-shelves equipments. The proposed method can be divided into two steps: the preprocessing and interpolation. In preprocessing step, first we capture image sequences from many different view angles, and store them with time relation in a special format called Multi-View Video. Then we extract feature points using SUSAN corner detection in each image, and design corresponding points algorithm to locate the corresponding feature points between each image pairs. Finally we use Delaunay Triangulation to produce a triangle mesh that is stored in an information file. In interpolation step, we use two files made in preprocessing (Multi-View Video and information file) and a technology similar to View Morphing to produce a virtual image sequence for an arbitrary viewpoint and view angle on real-time. In most traditional morphing methods, one creates virtual-viewpoint images by specifying reference points or reference lines manually. In our proposed method, however, virtual image sequence can be created automatically between any two existing image sequences.