scholarly journals Signal Phrase Extraction: A Gateway to Information Retrieval Improvement in Law Texts

2021 ◽  
Michael van der Veen ◽  
Natalia Sidorova

NLP-based techniques can support in improving understanding of legal text documents. In this work we present a semi-automatic framework to extract signal phrases from legislative texts for an arbitrary European language. Through a case study using Dutch legislation, we demonstrate that it is feasible to extract these phrases reliably with a small number of supporting domain experts. Finally, we argue how in future works our framework could be utilized with existing methods to be applied to different languages.

P A Bracewell ◽  
U R Klement

Piping design for ‘revamp’ projects in the process industry requires the retrieval of large amounts of ‘as-built’ data from existing process plant installations. Positional data with a high degree of accuracy are required. Photogrammetry, the science of measurement from photographs, was identified in Imperial Chemical Industries plc (ICI) as a suitable tool for information retrieval. The mathematical formulation enabling the definition of three-dimensional positions from photographic information is described. The process of using ICI's photogrammetric system for the definition of complete objects such as structures and pipes is illustrated. The need for specialized photogrammetric software for design purposes is explained. A case study describing how the photogrammetric system has been applied is described and graphical outputs from this exercise are shown. It is concluded that this particular photogrammetric system has proved to be a cost effective and accurate tool for the retrieval of ‘as-built’ information.

2021 ◽  
pp. 147387162110649
Javad Yaali ◽  
Vincent Grégoire ◽  
Thomas Hurtut

High Frequency Trading (HFT), mainly based on high speed infrastructure, is a significant element of the trading industry. However, trading machines generate enormous quantities of trading messages that are difficult to explore for financial researchers and traders. Visualization tools of financial data usually focus on portfolio management and the analysis of the relationships between risk and return. Beside risk-return relationship, there are other aspects that attract financial researchers like liquidity and moments of flash crashes in the market. HFT researchers can extract these aspects from HFT data since it shows every detail of the market movement. In this paper, we present HFTViz, a visualization tool designed to help financial researchers explore the HFT dataset provided by NASDAQ exchange. HFTViz provides a comprehensive dashboard aimed at facilitate HFT data exploration. HFTViz contains two sections. It first proposes an overview of the market on a specific date. After selecting desired stocks from overview visualization to investigate in detail, HFTViz also provides a detailed view of the trading messages, the trading volumes and the liquidity measures. In a case study gathering five domain experts, we illustrate the usefulness of HFTViz.

2018 ◽  
Vol 4 (s2) ◽  
Shigeto Kawahara ◽  
Seunghun J. Lee

AbstractThis paper analyzes the vocative truncation pattern in Korean from the viewpoint of Message-Oriented Phonology (MOP), which capitalizes on the idea that sound patterns are governed by a principle that makes message transfer effective. In the traditional naming pattern, Korean first names consist of a generation marker and a unique portion, and the order between these two elements alternates between generations. To derive vocative forms, the generation marker is truncated, and the suffixal [(j)a] is attached to the unique portion. We argue that MOP naturally predicts this type of truncation. As the generation marker is shared by all the members of the same generation, the generation marker is highly predictable and hence does not reduce uncertainty about the intended message. To achieve effective communication, predictable portions are deleted. Our analysis implies that MOP is relevant not only to phonetic implementation patterns, but also to morphophonological patterns. It also provides support for MOP based on data from a non-Indo-European language. Finally, we aim to integrate insights of MOP with a more formal proposal like Optimality Theory, by relating the predictability of a contrast to the ranking of the faithfulness constraint that it protects, following the spirit of the P-map hypothesis.

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