English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Upon film premiere, a major form of speculation concerns the relative successof the film. This relativity is in particular regards to the film's originalbudget, as many a time have big-budget blockbusters been met with exceptionalsuccess as met with abject failure. So how does one predict the success of anupcoming film? In this paper, we explored a vast array of film data in anattempt to develop a model that could predict the expected return of anupcoming film. The approach to this development is as follows: First, we beganwith the MovieLens dataset having common movie attributes along with genometags per each film. Genome tags give insight into what particularcharacteristics of the film are most salient. We then included additionalfeatures regarding film content, cast/crew, audience perception, budget, andearnings from TMDB, IMDB, and Metacritic websites. Next, we performedexploratory data analysis and engineered a wide range of new features capturinghistorical information for the available features. Thereafter, we used singularvalue decomposition (SVD) for dimensionality reduction of the high dimensionalfeatures (ex. genome tags). Finally, we built a Random Forest Classifier andperformed hyper-parameter tuning to optimize for model accuracy. A futureapplication of our model could be seen in the film industry, allowingproduction companies to better predict the expected return of their projectsbased on their envisioned outline for their production procedure, therebyallowing them to revise their plan in an attempt to achieve optimal returns.

Analyzing movies to predict their commercial viability for producers