Numeral Understanding in Financial Tweets for Fine-grained Crowd-based Forecasting

Numerals that contain much information in financial documents are crucial for financial decision making. They play different roles in financial analysis processes. This paper is aimed at understanding the meanings of numerals in financial tweets for fine-grained crowd-based forecasting. We propose a taxonomy that classifies the numerals in financial tweets into 7 categories, and further extend some of these categories into several subcategories. Neural network-based models with word and character-level encoders are proposed for 7-way classification and 17-way classification. We perform backtest to confirm the effectiveness of the numeric opinions made by the crowd. This work is the first attempt to understand numerals in financial social media data, and we provide the first comparison of fine-grained opinion of individual investors and analysts based on their forecast price. The numeral corpus used in our experiments, called FinNum 1.0 , is available for research purposes.Comment: Accepted by the 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2018), Santiago, Chil

Maintenance cost studies of rotary wing commercial transport aircraft

December 1974Includes bibliographical references (p. 121-123)Introduction: The vertical take-off and landing (VTOL) aircraft market has had substantial growth in the period of the last ten years when one considers the overall number of aircraft in use. The military fleet has continued to increase, as have such operators as natural resource (petroleum and lumber) companies, and law enforcement agencies. (See Table 1.) In scheduled passenger service, however, the VTOL- market has not enjoyed sustained growth. Consider Table 2, the type and number of helicopters in passenger service during 1962-1972. Following the cessation of federal subsidies to helicopter operators in 1966 the number of aircraft (and total available seats) has been steadily declining. Table 3 shows the composition of the fleets of the certificated carriers since 1966. Los Angeles Airways has been in bankruptcy since 1969; Chicago Helicopter is now largely a charter operator, although retaining its certificate; New York Airways, after a period of experimentation with the fixed wing Twin Otter (DHC-6) in 1968-1969, finally made it into the black in 1973, flying Sikorsky S-61's; and SFO Helicopter has retrenched its passenger services severely, but is not yet profitable. Why is the state of scheduled passenger operations so bleak? Many answers to this question have been given. For example, it has been said that the aircraft used by the operators have been inadequate: that they have been designed for military use and are ill suited for civilians who have been used to a higher comfort level (especially since most flights taken on a helicopter are in conjunction with a ride on a large, comfortable jet transport). Alternatively, it has been said that the high cost of operating the current helicopter fleet has caused the ticket price to be too high to be attractive to the traveler. Sometimes the operators have been fingered as the culprits -- that they have not priced their product adequately and have structured their networks poorly, i.e., that the failure has been one of management and marketing. And from the purely technology minded, the answer has been that once the properly designed rotary wing aircraft arrives on the scene -- one designed for civilian use and having the proper payload-range configuration -- the market will boom as VTOL aircraft enter city-center to city-center service. Doubtless there is a kernel -of truth in all these explanations, and examples to sustain most of them can be found in the history of helicopter operations in the United States. The intent of the work described in this report was to explore one frequently cited cause of the problem of high operating costs of helicopters in scheduled service - to wit, high maintenance costs of rotary wing aircraft. This attempt was made to allow a look ahead and to predict trends in maintenance costs of future rotary wing aircraft.This work was performed under a NASA Contract for Ames Research Cente

Fidelity-Enriched Contrastive Search: Reconciling the Faithfulness-Diversity Trade-Off in Text Generation

In this paper, we address the hallucination problem commonly found in natural language generation tasks. Language models often generate fluent and convincing content but can lack consistency with the provided source, resulting in potential inaccuracies. We propose a new decoding method called Fidelity-Enriched Contrastive Search (FECS), which augments the contrastive search framework with context-aware regularization terms. FECS promotes tokens that are semantically similar to the provided source while penalizing repetitiveness in the generated text. We demonstrate its effectiveness across two tasks prone to hallucination: abstractive summarization and dialogue generation. Results show that FECS consistently enhances faithfulness across various language model sizes while maintaining output diversity comparable to well-performing decoding algorithms.Comment: Accepted as a short paper at EMNLP 202

NumHG: A Dataset for Number-Focused Headline Generation

Headline generation, a key task in abstractive summarization, strives to condense a full-length article into a succinct, single line of text. Notably, while contemporary encoder-decoder models excel based on the ROUGE metric, they often falter when it comes to the precise generation of numerals in headlines. We identify the lack of datasets providing fine-grained annotations for accurate numeral generation as a major roadblock. To address this, we introduce a new dataset, the NumHG, and provide over 27,000 annotated numeral-rich news articles for detailed investigation. Further, we evaluate five well-performing models from previous headline generation tasks using human evaluation in terms of numerical accuracy, reasonableness, and readability. Our study reveals a need for improvement in numerical accuracy, demonstrating the potential of the NumHG dataset to drive progress in number-focused headline generation and stimulate further discussions in numeral-focused text generation.Comment: NumEval@SemEval-2024 Datase

FFTPL: An Analytic Placement Algorithm Using Fast Fourier Transform for Density Equalization

We propose a flat nonlinear placement algorithm FFTPL using fast Fourier transform for density equalization. The placement instance is modeled as an electrostatic system with the analogy of density cost to the potential energy. A well-defined Poisson's equation is proposed for gradient and cost computation. Our placer outperforms state-of-the-art placers with better solution quality and efficiency