arXiv subjects

Toshihiro Takahashi

Publications and source records attributed to Toshihiro Takahashi.

5 recordsLinked to original sources

arXiv2023

Matching of Descriptive Labels to Glossary Descriptions

Semantic text similarity plays an important role in software engineering tasks in which engineers are requested to clarify the semantics of descriptive labels (e.g., business terms, table column names) that are often consists of too short or too generic words and appears in their IT systems. We formulate this type of problem as a task of matching descriptive labels to glossary descriptions. We then propose a framework to leverage an existing semantic text similarity measurement (STS) and augment it using semantic label enrichment and set-based collective contextualization where the former is a method to retrieve sentences relevant to a given label and the latter is a method to compute similarity between two contexts each of which is derived from a set of texts (e.g., column names in the same table). We performed an experiment on two datasets derived from publicly available data sources. The result indicated that the proposed methods helped the underlying STS correctly match more descriptive labels with the descriptions.

cs.CL↗

arXiv2019

Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis

Recently, there has been a surge of interest in the use of machine learning to help aid in the accurate predictions of financial markets. Despite the exciting advances in this cross-section of finance and AI, many of the current approaches are limited to using technical analysis to capture historical trends of each stock price and thus limited to certain experimental setups to obtain good prediction results. On the other hand, professional investors additionally use their rich knowledge of inter-market and inter-company relations to map the connectivity of companies and events, and use this map to make better market predictions. For instance, they would predict the movement of a certain company's stock price based not only on its former stock price trends but also on the performance of its suppliers or customers, the overall industry, macroeconomic factors and trade policies. This paper investigates the effectiveness of work at the intersection of market predictions and graph neural networks, which hold the potential to mimic the ways in which investors make decisions by incorporating company knowledge graphs directly into the predictive model. The main goal of this work is to test the validity of this approach across different markets and longer time horizons for backtesting using rolling window analysis. In this work, we concentrate on the prediction of individual stock prices in the Japanese Nikkei 225 market over a period of roughly 20 years. For the knowledge graph, we use the Nikkei Value Search data, which is a rich dataset showing mainly supplier relations among Japanese and foreign companies. Our preliminary results show a 29.5% increase and a 2.2-fold increase in the return ratio and Sharpe ratio, respectively, when compared to the market benchmark, as well as a 6.32% increase and 1.3-fold increase, respectively, compared to the baseline LSTM model.

cs.LG↗

arXiv2019

Real-time tree search with pessimistic scenarios

Autonomous agents need to make decisions in a sequential manner, under partially observable environment, and in consideration of how other agents behave. In critical situations, such decisions need to be made in real time for example to avoid collisions and recover to safe conditions. We propose a technique of tree search where a deterministic and pessimistic scenario is used after a specified depth. Because there is no branching with the deterministic scenario, the proposed technique allows us to take into account the events that can occur far ahead in the future. The effectiveness of the proposed technique is demonstrated in Pommerman, a multi-agent environment used in a NeurIPS 2018 competition, where the agents that implement the proposed technique have won the first and third places.

cs.AI↗

arXiv2016

NMR Evidences for the coupling between conduction electrons and molecular degrees of freedom in the exotic member of the Bechgaard salt, (TMTSF)2FSO3

We performed Se and F-NMR measurements on single crystals of (TMTSF)2FSO3 to characterize the electronic structures of different phases in the Temperature-Pressure phase diagram, determined by precise transport measurements [Jo et al., Phys. Rev. B67, 014516 (2003)]. We claim that such varieties of electronic states in the refined phase diagram are caused by strong couplings of the conduction electrons with FSO3 anions, especially with the permanent electric dipoles on the anions. We suggest that as temperature decreases, the FSO3 anions form orientational ordering through two steps; first only the tetrahedrons form an orientational order leaving the orientations of the electronic dipoles in random (transition I); then the dipoles form a perfect orientational order at a lower temperature (transition II). In the intermediate temperature range between transitions I and II, we found an appreciable enhancement of homogeneous and inhomogeneous widths of 77Se-NMR spectrum. From the analysis of the angular dependence of the linewidth, we attributed these anomalies to the intramolecular charge disproportionation or imbalance and its slow dynamics caused by the coupling with the permanent electric dipole of anion. Results of 19F-NMR relaxation and lineshape measurements support this picture very well. Electronic structures at higher pressures up to 1.25 GPa are discussed on the basis of the results of the 77Se and 19F-NMR measurements.

cond-mat.str-el↗

arXiv2007

Charge Ordering in alpha-(BEDT-TTF)2I3 by synchrotron x-ray diffraction

The spatial charge arrangement of a typical quasi-two-dimensional organic conductor alpha-(BEDT-TTF)2I3 is revealed by single crystal structure analysis using synchrotron radiation. The results show that the horizontal stripe type structure, which was suggested by mean field theory, is established. We also find the charge disproportion above the metal-insulator transition temperature and a significant change in transfer integrals caused by the phase transition. Our result elucidates the insulating phase of this material as a 2k_F charge density localization.

cond-mat.str-el↗