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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,181 papers · 148 categories

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471114 · Jul 202019922001200920182026
48 results for movie revenue

Solves the film scheduling and staggered showtimes problem for movie theaters.

problem Maximize attendance and revenue by scheduling films with staggered showtimes.
method Binary integer linear optimization to find optimal schedules for each cluster of neighboring locations.
result Optimal scheduling cannot be done for all locations at once, but must be done for each cluster.

We present a grid diagram analogue of Carter, Rieger and Saito's smooth movie theorem. Specifically, we give definitions for grid movies, grid movie isotopies and present a definition of grid planar isotopy as a particular subset of the grid diagram moves: stabilization, destabilization and commutation. We show that gr…

2013-03-07abs ↗pdf ↗

Paper classifies movie genres using multimodal data.

problem Challenging task of multi-label movie genre classification.
method Created dataset from video clips, subtitles, synopses, and posters. Extracted features using various descriptors. Evaluated using different classifiers and late fusion strategy.
result Best F-Score result of 0.628 achieved by combining LSTM on synopses and CNN on movie trailer frames.

A movie multilayer network model captures narration from script, subtitles, and content.

problem Discovering content and stories in movies using network models.
method Developed a multilayer network model using visual and textual semantic cues.
result Demonstrated the effectiveness of the model on the Star Wars saga.

A shadow diagram is a knot diagram with under-over information omitted; a shadow movie is a sequence of shadow diagrams related by shadow Reidemeister moves. We show that not every shadow movie arises as the shadow of a Reidemeister movie, meaning a sequence of classical knot diagrams related by classical Reidemeister …

2011-06-17abs ↗pdf ↗

Machine learning predicts movie genres from summaries with high accuracy.

problem Predicting movie genres from plot summaries.
method Used Naive Bayes, Word2Vec+XGBoost, Recurrent Neural Networks, and Gated Recurrent Units (GRU) for text classification and multi-label problem.
result GRU neural networks achieve the best result with a Jaccard Index of 50.0%, F-score of 0.56, and hit rate of 80.5%.

Two singular links are cobordant if one can be obtained from the other by singular link isotopy together with a combination of births or deaths of simple unknotted curves, and saddle point transformations. A movie description of a singular link cobordism in 4-space is a sequence of singular link diagrams obtained from …

2015-07-15abs ↗pdf ↗

We present a marked analogue of Carter and Saito's movie theorem. Our definition of marking was chosen to coincide with the markings that arise in link Floer homology. In order to deal with complications arising from certain isotopies, we define three equivalence relations for marked surfaces and work over an equivalen…

2014-07-17abs ↗pdf ↗

This paper optimizes revenue and resource balance in network revenue management.

problem Maximizing revenue while ensuring fair resource consumption across different suppliers.
method Introduces a regularized revenue objective and a primal-dual UCB algorithm for continuous prices and balancing.
result Achieves a worst-case regret of O~(N5/2T)\widetilde O(N^{5/2}\sqrt{T}) for revenue maximization and balancing.

Improved video and movie description using multitask learning.

problem Lack of training data and poor generalization in video captioning.
method Multitask learning encoder-decoder framework for video sequences.
result Improved performance on multi-caption and single-caption datasets.

Study analyzes IMDB movie comments and Twitter data using machine learning and vector space techniques.

problem Sentiment analysis of IMDB movie comments and Twitter data.
method Created a vector space in KNIME Analytics platform, used Decision Trees, Naïve Bayes, and SVM algorithms for classification.
result SVM algorithm provided the best classification results for both IMDB movie comments and Twitter data sets.

The paper compares and improves aggregators for relational probabilistic models.

problem Predicting gender from movie ratings is challenging due to varying numbers of movies per user and users per movie.
method The paper compares existing aggregators and proposes new ones, showing their empirical superiority.
result New aggregators and model modifications outperform existing ones.

The paper introduces revenue uplift modeling to maximize marketing profits.

problem Maximizing incremental sales versus maximizing incremental revenue in marketing campaigns.
method Response transformation and two-stage models to decompose campaign profit.
result Revenue uplift modeling can improve campaign profit substantially.

Adapting momentum from optimization to reinforcement learning.

problem Improving the convergence and stability of reinforcement learning algorithms.
method Introducing Momentum Value Iteration (MoVI) by incorporating an average of consecutive state-action value functions, inspired by the concept of momentum in optimization.
result MoVI improves the convergence and stability of reinforcement learning algorithms, as demonstrated by experiments on Atari games.

This paper improves online ad revenue by optimizing auction performance directly.

problem Disconnection between ad ranking and auction performance in online advertising.
method Proposes new loss functions and ranking functions to maximize revenue.
result Proposed methods outperform state-of-the-art in maximizing platform revenue.

The paper proposes a new method for user-movie recommendation systems.

problem Improving recommendation accuracy in collaborative filtering.
method Uses Empirical Bayes with Reversible Jump Markov Chain in a Bayesian setup.
result Demonstrates improved hyper-parameter tuning and recommendation accuracy.

Germany's tax admin costs likely exceed 20% of total revenue, requiring system improvement.

problem High tax administrative costs in Germany and other jurisdictions.
method Statistical data, surveys, and a novel approach to measure total administrative cost as a percentage of total tax revenue.
result Germany's 2021 tax administrative costs likely exceeded 20% of total tax revenue.

The paper proposes a new method for product recommendation that considers revenue contributions and user similarity.

problem High dimensionality and sparsity in user-item data, especially in terms of revenue contributions.
method The approach encodes revenue contributions in the user-item matrix and computes customer similarity using suitable distance measures.
result The method segments users based on revenue-based similarity and supports recommendations aligned with profitability objectives.

This paper optimizes multi-channel sequential advertising to maximize cumulative revenue.

problem Maximizing cumulative revenue in multi-channel sequential advertising under a budget constraint.
method Formulated as a dynamic knapsack problem, proposed a bilevel optimization framework with action space reduction.
result Significantly improved cumulative revenue compared to state-of-the-art baselines.

This study improves valuation of post-revenue biopharmaceutical assets using Pfizer's data.

problem Accurate valuation of post-revenue drug assets in biotech and pharma.
method Historical sales data analysis to forecast future sales and calculate Net Present Value.
result Demonstrates a method for more informed investment decisions in biotech and pharma.

Proposes balancing revenue and environmental impact in assortment planning.

problem Maximizing revenue while considering environmental impact in retail assortment planning.
method Multi-objective optimization using Higg Material Sustainability Index.
result Shows it's possible to have lower environmental impact without significant revenue loss.

The study uses historical revenue data to forecast music catalog cashflows and multipliers.

problem Valuation of music catalogs based on historical revenue data.
method Risk-neutral approach using discounted cashflows formula.
result Ask prices are close to multipliers justified by median song cashflows, while best bids are near multipliers justified by bottom decile cashflows.

Predict missing movie ratings or graph embeddings with low rank matrices.

problem Predicting missing entries in a ratings matrix or graph embeddings with known linear relations.
method Low rank matrix completion approach applied to graph embeddings.
result Effective methods for predicting missing entries in matrices and graph embeddings.